研究者詳細 - 井上　創造

論文 - 井上　創造

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Optimizing Forecasted Activity Notifications with Reinforcement Learning 査読有り国際誌

Muhammad Fikry, Sozo Inoue

Sensors ( MDPI ) 23 ( 14 ) 6510 2023年07月

A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning 査読有り国際誌

ACM Transactions on Computer-Human Interaction ( ACM ) 30 ( 1-8 ) 1 - 27 2023年03月

Improving Noise Robustness of Single Sensor Data in Human Activity Recognition With UMAP and Additional Data 査読有り国際誌

Quynh Nguyen Phuong VU, Paula Lago, Sozo Inoue

ISWC '22: Proceedings of the 2022 ACM International Symposium on Wearable Computers ( ACM ) 109 - 111 2022年12月

Handling Class Imbalance in Forecasting Parkinson's Disease Wearing-off with Fitness Tracker Dataset 査読有り国際誌

John Noel Victorino, Sozo Inoue, Tomohiro Shibata

International Conference on Neural Information Processing (ICONIP2023) 564 - 578 2023年11月

Psychological Analysis in Human-Robot Collaboration from Workplace Stress Factors: A Review 査読有り国際誌

Nazmun Nahid, Xinyi Min, Md Atiqur Rahman Ahad, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

Summary of the Fourth Nurse Care Activity Recognition Challenge - Predicting Future Activities 査読有り国際誌

Defry Hamdhana, Chrisitina A Garcia, Nazmun Nahid, Haru Kaneko, Sayeda Shamma, Tahera Hossain, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

Improving Complex Nurse Care Activity Recognition Using Barometric Pressure Sensors 査読有り国際誌

Muhammad Fikry, Chrisitina A Garcia, Quynh N Phuong Vu, Shintaro Oyama, Keiko Yamashita, Yuji Sakamoto, Yoshinori Ideno, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

Challenges and Opportunities of Activity Recognition in Clinical Pathways 査読有り国際誌

Chrisitina A Garcia, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

Analysis of Care Records for Predicting Urination Times 査読有り国際誌

Masato Uchimura, Haru Kaneko, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

Forecasting Parkinson's Disease Patients' Wearing-Off using Wrist-Worn Fitness Tracker and Smartphone Dataset 査読有り国際誌

John Noel C Victorino, Yuko Shibata, Sozo Inoue, Tomohiro Shibata

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

Understanding Mental Health Using Ubiquitous Sensors and Machine Learning: Challenges Ahead 査読有り国際誌

Activity and Behavior Computing (to appear) ( CRC press ) 2023年06月

PerMML: A Performance Metric for Multi-layer Dataset 査読有り国際誌

Sayeda Shamma Alia, Tahera Hossain, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021年09月

Summary of the Third Nurse Care Activity Recognition Challenge - Can We Do from the Field Data? 査読有り国際誌

Sayeda Shamma Alia, 安達康平, Tahera Hossain, Le Nhat Tan, 金子晴, Paula Lago, 大北剛, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021年09月

Transition-points-based Segmentation and Hierarchical Classification for Locomotion and Transportation recognitionon Radio-data 査読有り国際誌

Le Nhat Tan, Nazmun Nahid, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021年09月

Analysis of Feature Importances for Automatic Generation of Care Records 査読有り国際誌

金子晴, Tahera Hossain, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021年09月

Integrating A Spoken Dialogue System, Nursing Records, and Activity Data Collection based on Smartphones 査読有り国際誌

ティッタヤ　マイリッタ, Nattaya Mairittha, 井上創造

Computer Methods and Programs in Biomedicine, ISSN 0169-2607 106364 2021年08月

記述言語：英語掲載種別：研究論文（学術雑誌）

Background and Objective: This study describes the integration of a spoken dialogue system and nursing records on an Android smartphone application intending to help nurses reduce documentation time and improve the overall experience of a healthcare setting. The application also incorporates with collecting personal sensor data and activity labels for activity recognition. Methods: We developed a joint model based on a bidirectional long-short term memory and conditional random fields (Bi-LSTM-CRF) to identify user intention and extract record details from user utterances. Then, we transformed unstructured data into record inputs on the smartphone application. Results: The joint model achieved the highest F1-score at 96.79%. Moreover, we conducted an experiment to demonstrate the proposed models capability and feasibility in recording in realistic settings. Our preliminary evaluation results indicate that when using the dialogue-based, we could increase the percentage of documentation speed to 58.13% compared to the traditional keyboard-based. Conclusions: Based on our findings, we highlight critical and promising future research directions regarding the design of the efficient spoken dialogue system and nursing records.

Kyutacar

その他リンク： https://doi.org/10.1016/j.cmpb.2021.106364.

Intracranial Hemorrhage Brain Image Non-rigid Registration from Real-world Dataset to Reference Space 査読有り国際誌

Le Nhat Tan, 小橋昌司, 有村公一, 飯原弘二, 井上創造

International Conference on Imaging, Vision & Pattern Recognition (IVPR) 7 pages 2021年08月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Online Online

Intracranial Hemorrhage is a common brain injury that leads to a high mortality rate without prompt recognition. To address these issues, computer-aid diagnosis tools are rapidly being developed along with neural-network-based techniques to provide fast, reliable analysis and achieve accurate diagnosis decisions based on medical images. One of the most interesting applications in computer-aid diagnosis is Image Registration due to its practical features in clinical diagnosis and treatment planning. In this study, we present the non-rigid image registration for the 3D Computed Tomography image dataset of the Intracranial Hemorrhage Brain. By utilizing the affine transformation and a neural network model, we aim to predict the deformation vector field, map the real-world-collected dataset to the reference space and overcome the shifting data problem between the data analysis experiment on standard and real-world medical image analysis. Our test results gave that good registration performance is obtained in a very short time by using a neural network model, and the affine transformation significantly improves the real-world image registration. In addition, according to the distance from the hematoma area change ratio to the brain area change ratio, the characteristics of the major structure are determined to be preserved.

Predicting Wearing-Off of Parkinson’s Disease Patients Using a Wrist-Worn Fitness Tracker and a Smartphone: A Case Study 査読有り国際誌

John Noel Victorino, Yuko Shibata, 井上創造, 柴田智広

Applied Sciences, MDPI 11 ( 16 ) 2 - 2 2021年08月

記述言語：英語掲載種別：研究論文（学術雑誌）

Parkinson’s disease (PD) patients experience varying symptoms related to their illness. Therefore, each patient needs a tailored treatment program from their doctors. One approach is the use of anti-PD medicines. However, a “wearing-off” phenomenon occurs when these medicines lose their effect. As a result, patients start to experience the symptoms again until their next medicine intake. In the long term, the duration of “wearing-off” begins to shorten. Thus, patients and doctors have to work together to manage PD symptoms effectively. This study aims to develop a prediction model that can determine the “wearing-off” of anti-PD medicine. We used fitness tracker data and self-reported symptoms from a smartphone application in a real-world environment. Two participants wore the fitness tracker for a month while reporting any symptoms using the Wearing-Off Questionnaire (WoQ-9) on a smartphone application. Then, we processed and combined the datasets for each participant’s models. Our analysis produced prediction models for each participant. The average balanced accuracy with the best hyperparameters was at 70.071.7% for participant 1 and 76.176.9% for participant 2, suggesting that our approach would be helpful to manage the “wearing-off” of anti-PD medicine, motor fluctuations of PD patients, and customized treatment for PD patients. View Full-Text

Kyutacar

その他リンク： https://www.mdpi.com/2076-3417/11/16/7354

CrowdAct: Achieving High-Quality Crowdsourced Datasets in Mobile Activity Recognition 査読有り国際誌

Nattaya Mairittha, ティッタヤ　マイリッタ, 井上創造

Proc. of ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Article 142, 5 ( 0 ) 3 - 2 2021年03月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this study, we propose novel gamified active learning and inaccuracy detection for crowdsourced data labeling for an activity recognition system using mobile sensing (CrowdAct). First, we exploit active learning to address the lack of accurate information. Second, we present the integration of gamification into active learning to overcome the lack of motivation and sustained engagement. Finally, we introduce an inaccuracy detection algorithm to minimize inaccurate data. To demonstrate the capability and feasibility of the proposed model in realistic settings, we developed and deployed the CrowdAct system to a crowdsourcing platform. For our experimental setup, we recruited 120 diverse workers. Additionally, we gathered 6,549 activity labels from 19 activity classes by using smartphone sensors and user engagement information. We empirically evaluated the quality of CrowdAct by comparing it with a baseline using techniques such as machine learning and descriptive and inferential statistics. Our results indicate that CrowdAct was effective in improving activity accuracy recognition, increasing worker engagement, and reducing inaccurate data in crowdsourced data labeling. Based on our findings, we highlight critical and promising future research directions regarding the design of efficient activity data collection with crowdsourcing.

Kyutacar

その他リンク： https://dl.acm.org/doi/abs/10.1145/3432222

私のブックマーク「センサを用いた行動認識」

井上創造

人工知能 36 ( 2 ) 233 - 246 2021年03月

Estimation of Record Contents for Automatic Generation of Care Records 査読有り国際誌

金子晴, Tahera Hossain, 井上創造

Activity and Behavior Computing, Springer Nature 289 - 306 2021年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Elderly person are increasing all over the world. Smart nursing facilities
are required to support them for their good health.Especially in Japan, it is essential to
have automated nursing facilities center to support the relentlessly increasing elderly
person all over the country.As long as elderly people are increasing, the demand for
nursing care services are also increasing day by day.There is a shortage of nurse
to support this vast elderly people.In order to resolve the shortage of nurse, it is
important to reduce the work load for nurse.There are some research to simplify the
care recording process.The main approach is activity recognition or the development
of new apps. However, we aimed for automatic generation of the care records of near
future. So in this paper, we evaluate the accuracy of the automatic generation of
care records using care record data from real nursing facility to simplify the task of
making care records.We made two machine learning models to estimate the "target
patient" and the "recorded value" of care records.And we evaluated the classification
result from the data collected by the care record app.We used two months of data we
collected from Japanese nursing facility for the evaluation.We can achieve, average
F1-score of ’target patient’ estimation is 74% and the average F1-score of ’detail of
record’ estimation is 58%. We believe that using these results in care records app
will simplify the task of making care records.

その他リンク： https://link.springer.com/chapter/10.1007/978-981-15-8944-7_18

Multilabel Classification of Nursing Activities in a Realistic Scenario 査読有り国際誌

Farina Faiz, 出野義則, 井上創造

Activity and Behavior Computing, Springer Nature 269 - 288 2021年01月

Exploring Human Activities Using eSense Earable Device 査読有り国際誌

Md. Shafiqul Islam, Tahera Hossain, Md Atiqur Rahman Ahad, 井上創造

Activity and Behavior Computing, Springer Nature 169 - 185 2021年01月

Improvement of Human Action Recognition Using 3D Pose Estimation 査読有り国際誌

安達康平, Paula Lago, 大北剛, 井上創造

Activity and Behavior Computing, Springer Nature 21 - 37 2021年01月

Summary of the Cooking Activity Recognition Challenge 査読有り国際誌

Sayeda Shamma Alia, Paula Lago, 武田紳吾, 安達康平, Brahim Benaissa, Md Atiqur Rahman Ahad, 井上創造

Human Activity Recognition Challenge, Springer Nature 1 - 13 2021年01月

On-Device Deep Personalization for Robust Activity Data Collection 査読有り国際誌

Nattaya Mairittha, ティッタヤ　マイリッタ, 井上創造

Sensors, MDPI 21 ( 41 ) 2 - 2 2020年12月

記述言語：英語掲載種別：研究論文（学術雑誌）

One of the biggest challenges of activity data collection is the need to rely on users and keep them engaged to continually provide labels. Recent breakthroughs in mobile platforms have proven effective in bringing deep neural networks powered intelligence into mobile devices. This study proposes a novel on-device personalization for data labeling for an activity recognition system using mobile sensing. The key idea behind this system is that estimated activities personalized for a specific individual user can be used as feedback to motivate user contribution and improve data labeling quality. First, we exploited fine-tuning using a Deep Recurrent Neural Network to address the lack of sufficient training data and minimize the need for training deep learning on mobile devices from scratch. Second, we utilized a model pruning technique to reduce the computation cost of on-device personalization without affecting the accuracy. Finally, we built a robust activity data labeling system by integrating the two techniques outlined above, allowing the mobile application to create a personalized experience for the user. To demonstrate the proposed model’s capability and feasibility, we developed and deployed the proposed system to realistic settings. For our experimental setup, we gathered more than 16,800 activity windows from 12 activity classes using smartphone sensors. We empirically evaluated the proposed quality by comparing it with a baseline using machine learning. Our results indicate that the proposed system effectively improved activity accuracy recognition for individual users and reduced cost and latency for inference for mobile devices. Based on our findings, we highlight critical and promising future research directions regarding the design of efficient activity data collection with on-device personalization.

Kyutacar

その他リンク： https://doi.org/10.3390/s21010041

Implementation of Care Records Automatic Generation Function in a Care Record Application 査読有り国際誌

金子晴, Tahera Hossain, 井上創造

The 40th Joint Conference on Asia-Pacific Association of Medical Informatics (APAMI) 6 pages 2020年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Online Online

The number of elderly people is increasing in the world. Especially in Japan, the shortage of nurses has been a problem in recent years. So far, we had developed a mobile application to make nursing care records. In addition, we are also experimenting with the introduction of this application to nursing homes. In this paper, we design an automatic generation function of the nursing care record into our mobile nursing care record application. In this paper, we implement an automatic generation function of the recorded contents in this care record system. we aim to simplify the work of making care records. To do so, we make a machine learning model for estimating the feature nursing care records in the server. And, we design new UI on our application to make care records using estimation result. As a result of the evaluation, we know it is possible to reduce time that making care records using our application with automatic generation function of care records.

Activity Recognition for Assisting People with Dementia 査読有り国際誌

Muhammad Fikry, Defry Hamdhana, Paula Lago, 井上創造

Contactless Human Activity Analysis, Springer Nature 0 2 - 2 2020年12月

記述言語：英語掲載種別：研究論文（学術雑誌）

Online Online

Technology can help and provide support to people with dementia to ensure their safety during daily
activities. In this paper, we summarize information about activity recognition for people living with
dementia. This paper aims to understand the uses and types of applications, the types of sensors/systems,
methods, and data used within the scope of human activity recognition to monitor, detect symptoms, or
help people with dementia. To this end, 447 abstracts were collected from a Scopus database, which
yielded 127 relevant papers and 102 papers that were considered in detail based on the four categories of
assessment (application, system/sensors, methods, and data). This paper shows the trend that smart
environment technology is most widely used for monitoring people with dementia, wherein machine
learning techniques as a method for activity recognition to achieve the results of testing or implementing
the system. We conclude that combining sensor devices and the addition of smartphone devices in one
system is suitable for implementation because it can be used as an identity such that it distinguishes the
object under study with other objects. During the monitoring process, prevention can be achieved
simultaneously by adding a warning alarm in the smartphone when people with dementia perform
abnormal activities, and the results need to be further analyzed to get the best pattern of activities for
people with dementia. Next, the type of application that was initially designed for monitoring can be
developed into an assistant for people with dementia.

Enhancing Nursing Care Records with A Spoken Dialogue System based on Smartphones 査読有り国際誌

ティッタヤ　マイリッタ, Nattaya Mairittha, 井上創造

The 40th Joint Conference on Asia-Pacific Association of Medical Informatics (APAMI) 8 pages 2020年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Background and Objective: This study describes the integration of a spoken dialogue system and
nursing records on an Android smartphone application intending to help nurses reduce documentation
time and improve the overall experience of a healthcare setting. The application also incorporates with
collecting personal sensor data and activity labels for activity recognition.
Methods: We developed a joint model based on a bidirectional long-short term memory and conditional random fields (Bi-LSTM-CRF) to identify user intention and extract record details from user
utterances. Then, we transformed unstructured data into record inputs on the smartphone application.
Results: The joint model achieved the highest F1-score at 96.79%. Moreover, we conducted an experiment to demonstrate the proposed model’s capability and feasibility in recording in realistic settings.
Our preliminary evaluation results indicate that when using the dialogue-based, we could increase the
percentage of documentation speed to 58.13% compared to the traditional keyboard-based.
Conclusions: Based on our findings, we highlight critical and promising future research directions
regarding the design of the efficient spoken dialogue system and nursing records.

Mobile application for caregiver in collecting statistical data of BPSD attack focused on macro activities: PhD forum abstract 査読有り国際誌

Defry Hamdhana

Proceedings of the Conference on Embedded Networked Sensor Systems (SenSys) 807 - 808 2020年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Yokohama (virtual)

BPSD affects Dementia patients often and varies. It is needed a best and suit treatment from doctors to handle BPSD attack toward Dementia patients. Therefore, to obtain accurate data of patients in daily care, caregivers are expected to conduct ...

その他リンク： https://doi.org/10.1145/3384419.3430577

Multilabel classification in human activity recognition: PhD forum abstract 査読有り国際誌

Farina Faiz

Proceedings of the Conference on Embedded Networked Sensor Systems (SenSys) 809 - 810 2020年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Yokohama (virtual)

Human activities become very difficult to handle when they appear without proper temporal information. A smarter approach is to handle this problem is using multilabel classification. However, most of the multilabel methods are suitable for text data ...

その他リンク： https://doi.org/10.1145/3384419.3430578

Requirements analysis for reminder system in daily activity recognition dementia: PhD forum abstract 査読有り国際誌

Muhammad Fikry

Proceedings of the Conference on Embedded Networked Sensor Systems (SenSys) 815 - 816 2020年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Yokohama (virtual)

Technology assistance refers to all tools or systems that allow a people with dementia to carry out their daily activities in order to increase convenience and security in these activities. Dementia is a condition of a collection of symptoms of irreversible brain damage that occurs over a relatively long time period, resulting in problems concentrating, planning or organizing daily activities. This paper is focused on estimating daily activity recognition time by considering the feasibility of activity types, feature extraction techniques for speech recognition, and the design effectiveness of a system that is easy to use by people with dementia. The results from activity recognition need to be further analyzed to find the best pattern for people with dementia. After that, monitoring applications can develop into prevention of abnormal activity in dementia.

その他リンク： https://doi.org/10.1145/3384419.3430572

Improving Activity Data Collection with On-device Personalization Using Fine-tuning 査読有り国際誌

Nattaya Mairittha, ティッタヤ　マイリッタ, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 255 - 260 2020年09月

Improving Fine-tuned Question Answering Models for Electronic Health Records 査読有り国際誌

ティッタヤ　マイリッタ, Nattaya Mairittha, 井上創造

Ubicomp Workshop on Computing for Well-Being (WellComp) 688 - 691 2020年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Mexico (virtual) Mexico (virtual)

The prevalence of voice assistants has strengthened the interest in a
question answering for the medical domain, allowing both patients
and healthcare providers to enter a question naturally and pinpoint
useful information quickly. However, a large number of medical
terms makes the creation of such a system a demanding task. To
address this challenge, we explore transfer learning techniques
for constructing a personalized EHR-QA system. The goal is to
answer questions regarding a discharge summary in an electronic
health record (EHR). We present the experiments with a pre-trained
BERT (Bidirectional Encoder Representations from Transformers)
model fine-tuned on different tasks and show the results obtained
to provide insights into learning effects and training effectiveness.

Kyutacar

その他リンク： https://doi.org/10.1145/3410530.3414436

MCoMat: a New Performance Metric for Imbalanced Multi-layer Activity Recognition Dataset 査読有り国際誌

Sayeda Shamma Alia, Paula Lago, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 232 - 237 2020年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Mexico (virtual) Mexico (virtual)

Existing performance metrics assess classifiers on single granularity layer. Having multi-layer labels is also possible such as activity recognition datasets. Semantic annotations could be given with multiple granularity layers in these datasets e.g., ...

Kyutacar

その他リンク： https://doi.org/10.1145/3410530.3414364

Summary of the 2nd Nurse Care Activity Recognition Challenge Using Lab and Field Data 査読有り国際誌

Sayeda Shamma Alia, Paula Lago, 安達康平, Tahera Hossain, 後藤広樹, 大北剛, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 378 - 383 2020年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Mexico (virtual) Mexico (virtual)

2nd Nurse Care Activity Recognition Challenge using Lab and Field Data is organized as a part of HASCA workshop and is continuation of Nurse Care Activity Recognition Challenge [7]. We give the description of the dataset and summarize the approaches ...

Kyutacar

その他リンク： https://doi.org/10.1145/3410530.3414611

WorkerSense: Mobile Sensing Platform for Collecting Physiological, Mental, and Environmental State of Office Workers 査読有り国際誌

谷優里, Shuichi Fukuda, 松田裕貴, 井上創造

PerHealth 2020: 5th IEEE PerCom Workshop on Pervasive Health Technologies (PerHealth 2020) 2020年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

In data collection of the human physiological and psychological conditions
for mental healthcare (e.g., work engagement), measurement methods using
environment-installed sensors and questionnaire surveys have been often
used. However, these approaches are not practical in continuous data
collection, due to the large burden for people. Recently, in association
with advancing sensing technology with IoTs, sensing by small sensors and
wearable devices has become possible easily. In this paper, we
aim to establish a simple and general sensing method based on a mobile
application for measuring physiological and psychological state of office
workers and environmental state. Through the experiment for 2-3 weeks
involving 60 office workers of four Japanese companies by using our
application, we succeeded to create a dataset of physiological,
environment, and mental state. This paper explains the developed mobile
application, experimental procedure, and a summary of the data collected in
the experiment.

Automatic Labeled Dialogue Generation for Nursing Record Systems 査読有り国際誌

ティッタヤ　マイリッタ, Nattaya Mairittha, 井上創造

JPM Journal of Personalized Medicine 10 ( 3 ) 6 - 2 2020年09月

記述言語：英語掲載種別：研究論文（学術雑誌）

The integration of digital voice assistants in nursing residences is becoming increasingly important to facilitate nursing productivity with documentation. A key idea behind this system is training natural language understanding (NLU) modules that enable the machine to classify the purpose of the user utterance (intent) and extract pieces of valuable information present in the utterance (entity). One of the main obstacles when creating robust NLU is the lack of sufficient labeled data, which generally relies on human labeling. This process is cost-intensive and time-consuming, particularly in the high-level nursing care domain, which requires abstract knowledge. In this paper, we propose an automatic dialogue labeling framework of NLU tasks, specifically for nursing record systems. First, we apply data augmentation techniques to create a collection of variant sample utterances. The individual evaluation result strongly shows a stratification rate, with regard to both fluency and accuracy in utterances. We also investigate the possibility of applying deep generative models for our augmented dataset. The preliminary character-based model based on long short-term memory (LSTM) obtains an accuracy of 90% and generates various reasonable texts with BLEU scores of 0.76. Secondly, we introduce an idea for intent and entity labeling by using feature embeddings and semantic similarity-based clustering. We also empirically evaluate different embedding methods for learning good representations that are most suitable to use with our data and clustering tasks. Experimental results show that fastText embeddings produce strong performances both for intent labeling and on entity labeling, which achieves an accuracy level of 0.79 and 0.78 f1-scores and 0.67 and 0.61 silhouette scores, respectively.

Kyutacar

その他リンク： https://doi.org/10.3390/jpm10030062

Towards Mapping Activity Classes for Transfer Learning in Human Activity Recognition 査読有り国際誌

Md. Shafiqul Islam, Sayeda Shamma Alia, 井上創造

International Conference on Activity and Behavior Computing (ABC) 5 pages 2020年08月

Synthesizing Cell Protein data for Human Protein Cell Profiling Using Dual Deep Generative Modeling 査読有り国際誌

Rakesh Ranjan, 井上創造, 柴田智広

International Conference on Imaging, Vision & Pattern Recognition (IVPR) 1 - 6 2020年08月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Kitakyushu

To understand the biology of health, and how molecular dysfunction leads to disease, knowledge of the human cell is essential. The protein is the core unit of the human body made from trillions of cells, forming the body's various tissues. These tissues come together to create human organs. It is essential to understand the Spatio-temporal distribution of proteins in cells and to investigate human RNA-sequencing for human genes characterization. For this, it requires a massive amount of annotated data. However, due to many considerations like the high cost of data sample collection, lack of data sample availability, and lawful clauses for patient privacy, the majority of medical data is out of reach for general public research. In this study, we propose a new dual deep generative method for synthesizing human cell protein images by using the Generative Adversarial Network technique. Specifically, for that, we pair original cell protein images with their respective Cell-protein-tree. These pairs are then used to learn the mapping from a binary cell protein to a new cell protein image. For this purpose, we use an image-to-image translation technique based on adversarial learning. The generated cell protein images are expected to preserve the structural and visual quality of the training images. Visual and quantitative analysis of the experimental results demonstrates that the synthesized data are preserving the desired quality while maintaining the different forms of original data. Contribution-We have proposed a new dual deep generative model for synthesizing cell protein data.

その他リンク： https://ieeexplore.ieee.org/document/9306574

Exploring the Use of Accelerometer for Assisting Weight Lifting Exercise 査読有り国際誌

Nour Al Bogha, 井上創造, Brahim Benaissa

International Conference on Activity and Behavior Computing (ABC) 1 - 4 2020年08月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Japan Kitakyushu

One of the most important aspects of professional athleticism and rehabilitation is muscle activation. Although sport tracking technologies are advancing
rapidly, existing technologies and devices for detecting muscle performance are still
out of common users’ hands, due to their complexity, invasive nature and high cost.
However, sensor equipped devices are getting widely available, which opens the
door to alternative solutions using software. In this work we explore the possibility
of using accelerometer data for muscle performance in a weightlifting exercise. By
investigating a predefined common weightlifting exercise, we exploited a correlation between the acceleration and the lifted weights using a simple RBF prediction
method, in a real experiment where data obtained from three participants. The obtained results show that the weight could be predicted in acceptable accuracy for
each individual, based on acceleration data.

その他リンク： https://abc-research.github.io/2020/

Towards New Performance Metrics for Multi-level Data for Activity Recognition 査読有り国際誌

Sayeda Shamma Alia, Paula Lago, 井上創造

International Conference on Activity and Behavior Computing (ABC) 1 - 8 2020年08月

A Method for Sensor-Based Activity Recognition in Missing Data Scenario 査読有り国際誌

Tahera Hossain, Md Atiqur Rahman Ahad, 井上創造

Sensors 20 ( 3811 ) 2 - 3 2020年07月

Wearable Sensor-Based Gait Analysis for Age and Gender Estimation 査読有り国際誌

Md Atiqur Rahman Ahad, Thanh Trung Ngo, Anindya Das Antar, Masud Ahmed, Tahera Hossain, Daigo Muramatsu, Yasushi Makihara, 井上創造, Yasushi Yagi

Sensors 20 ( 2424 ) 2 - 4 2020年04月

2050年の情報処理：7. 近未来を予測できる世界，Ability-awareな世界

井上創造

情報処理 61 ( 5 ) 453 - 455 2020年04月

担当区分：筆頭著者記述言語：日本語掲載種別：記事・総説・解説・論説等（学術雑誌）

本稿では，2050年の情報処理について，応用の観点から，以下の5点を展望した．それは，1.現在の機械学習技術の延長線上で，少し先の未来を予測する近未来予測技術が発展するだろうこと，2.原理研究だけではなく，手法に新規性がなくとも社会実装した結果得られた知見も重視すべきであること，3.伝統ある統計的仮説検定は30年後には廃れているであろうこと，4.身体的な人間拡張に加え，情報的な人間拡張のための，Ability-aware技術が確立しているであろうこと，5.現在の散在する情報プラットフォームが30年後にどれだけ継続されているかという懸念，である．

Kyutacar

その他リンク： http://id.nii.ac.jp/1001/00204305/

医療と介護のIoT

井上創造

総合リハビリテーション, 医学書院 48 ( 1 ) 35 - 41 2020年01月

Characterizing Word Embeddings for Zero-Shot Sensor-Based Human Activity Recognition 査読有り国際誌

松木萌, Paula Lago, 井上創造

MDPI Sensors 19 ( 22 ) 1 - 26 2019年11月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, we address Zero-shot learning for sensor activity recognition using word embeddings. The goal of Zero-shot learning is to estimate an unknown activity class (i.e., an activity that does not exist in a given training dataset) by learning to recognize components of activities expressed in semantic vectors. The existing zero-shot methods use mainly 2 kinds of representation as semantic vectors, attribute vector and embedding word vector. However, few zero-shot activity recognition methods based on embedding vector have been studied; especially for sensor-based activity recognition, no such studies exist, to the best of our knowledge. In this paper, we compare and thoroughly evaluate the Zero-shot method with different semantic vectors: (1) attribute vector, (2) embedding vector, and (3) expanded embedding vector and analyze their correlation to performance. Our results indicate that the performance of the three spaces is similar but the use of word embedding leads to a more efficient method, since this type of semantic vector can be generated automatically. Moreover, our suggested method achieved higher accuracy than attribute-vector methods, in cases when there exist similar information in both the given sensor data and in the semantic vector; the results of this study help select suitable classes and sensor data to build a training dataset.

DOI： 10.3390/s19225043

Kyutacar

その他リンク： https://doi.org/10.3390/s19225043

Human Activity Recognition using Earable Device 査読有り

Tahera Hossain, Md. Shafiqul Islam, Md Atiqur Rahman Ahad, 井上創造

ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) 5 2019年09月

Optimizing Activity Data Collection with Gamification Points Using Uncertainty Based Active Learning 査読有り

Nattaya Mairittha, Tittaya Marittha , 井上創造

International Workshop on Human Activity Sensing Corpus and Applications 7 pages 2019年09月

Nurse Care Activity Recognition Challenge: Summary and Results 査読有り

Paula Lago, Sayeda Shamma Alia, 武田紳吾, Tittaya Marittha , Nattaya Mairittha, Farina Faiz, 西村勇亮, 安達康平, 大北剛, Franois Charpillet , 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 6 pages 2019年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

London London

Although activity recognition has been studied for a long time now, research and applications have focused on physical activity recognition. Even if many application domains require the recognition of more complex activities, research on such activities has attracted less attention.
One reason for this gap is the lack of datasets to evaluate and compare different methods.
To promote research in such scenarios, we organized the \textit{Open Lab Nursing Activity Recognition Challenge} focusing on the recognition of complex activities related to the nursing domain. Nursing domain is one of the domains that can benefit enormously from activity recognition but has not been researched due to lack of datasets.
The competition used the CARECOM Nurse Care Activity Dataset, featuring 7 activities performed by 8 subjects in a controlled environment with accelerometer sensors, motion capture and indoor location sensor.
In this paper, we summarize the results of the competition.

Kyutacar

Reduction of Marker-Body Matching Work in Activity Recognition Using Motion Capture 査読有り

武田紳吾, Paula Lago, 大北剛, 井上創造

International Workshop on Human Activity Sensing Corpus and Applications ７ pages 2019年09月

A Dialogue-Based Annotation for Activity Recognition 査読有り

Tittaya Marittha , Nattaya Mairittha, 井上創造

International Workshop on Human Activity Sensing Corpus and Applications 6 pages 2019年09月

スマートライフケア社会創造のための基盤づくり

柴田智広, 井上創造, 相馬功

システム制御情報学会誌 ( システム制御情報学会誌 ) 2019年09月

Evaluation of Transfer Learning for Human Activity Recognition among Different Datasets 査読有り

Md. Shafiqul Islam, 大北剛, 井上創造

International Conference on Pervasive Intelligence and Computing (2019) (IEEE PICom 2019) 2019年08月

On-Device Deep Learning Inference for Efficient Activity Data Collection 査読有り

Nattaya Mairittha, Tittaya Marittha , 井上創造

Sensors 19 ( 15 ) 2 - 0 2019年08月

記述言語：英語掲載種別：研究論文（学術雑誌）

Labeling activity data is a central part of the design and evaluation of human activity recognition systems. The performance of the systems greatly depends on the quantity and “quality” of annotations; therefore, it is inevitable to rely on users and to keep them motivated to provide activity labels. While mobile and embedded devices are increasingly using deep learning models to infer user context, we propose to exploit on-device deep learning inference using a long short-term memory (LSTM)-based method to alleviate the labeling effort and ground truth data collection in activity recognition systems using smartphone sensors. The novel idea behind this is that estimated activities are used as feedback for motivating users to collect accurate activity labels. To enable us to perform evaluations, we conduct the experiments with two conditional methods. We compare the proposed method showing estimated activities using on-device deep learning inference with the traditional method showing sentences without estimated activities through smartphone notifications. By evaluating with the dataset gathered, the results show our proposed method has improvements in both data quality (i.e., the performance of a classification model) and data quantity (i.e., the number of data collected) that reflect our method could improve activity data collection, which can enhance human activity recognition systems. We discuss the results, limitations, challenges, and implications for on-device deep learning inference that support activity data collection. Also, we publish the preliminary dataset collected to the research community for activity recognition.

Kyutacar

その他リンク： https://www.mdpi.com/1424-8220/19/15/3434

A Comparative Study on Missing Data Handling Using Machine Learning for Human Activity Recognition 査読有り

Tahera Hossain, 井上創造

International Conference on Activity and Behavior Computing 6 pages 2019年05月

Integrating Activity Recognition and Nursing Care Records: the System, Experiment, and the Dataset 査読有り

井上創造, Tittaya Marittha , Nattaya Mairittha, Tahera Hossain

International Conference on Activity and Behavior Computing 6 pages 2019年05月

Crowdsourcing System Management for Activity Data with Mobile Sensors 査読有り

Nattaya Mairittha, 井上創造

International Conference on Activity and Behavior Computing 6 pages 2019年05月

Toward Projection Learning between Sensor Data and Semantic Word Vector for Zero-shot Learning 査読有り

松木萌, 井上創造

International Conference on Activity and Behavior Computing 6 pages 2019年05月

Comparing Feature Learning Methods for Human Activity Recognition: Performance Study in New User Scenario 査読有り

Paula Lago, 井上創造

International Conference on Activity and Behavior Computing 5 pages 2019年05月

Sensor-based Daily Activity Understanding in Caregiving Center 査読有り

Tahera Hossain, 井上創造

IEEE PerCom Student Forum 2 pages 2019年03月

IoT行動認識技術の実用化とオープンイノベーションへの取り組み

井上創造, 房前悟, 相馬功, 柴田智広

計測自動制御学会誌 ( 計測自動制御学会誌 ) 2019年02月

A Hybrid Model Using Hidden Markov Chain and Logic Model for Daily Living Activity Recognition 査読有り

Paula Lago, 井上創造

International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2018) 4 - 7 2018年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Punta Cana, Dominican Republic Punta Cana, Dominican Republic

We detail the solution to the UCAmI Cup Challenge to recognizing on going activities at home from sensor measurements. We use binary sensors and proximity sensor measurements for the recognition. We use an hybrid strategy, combining a probabilistic model and a definition-based model. The former consists of a Hidden Markov Model using the result of a neural network as emission probabilities. It is trained with the labelled data provided by the Cup. The latter approach takes advantage of the descriptions provided for each of the activities which are expressed in logical statements based on the sensors states. We then combine the results with a weighted average. We compare the performance of each individual strategy and of the combined strategy.

Kyutacar

その他リンク： https://www.mdpi.com/2504-3900/2/19/1266

IoT技術の医療介護への応用

井上創造

日医雑誌 ( 日医雑誌 ) 147 ( 8 ) 1619 - 1622 2018年11月

Activity Recognition: Translation Across Sensor Modalities Using Deep Learning

大北剛, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 1462 - 1471 2018年10月

Supervised and Neural Classifiers for Locomotion Analysis 査読有り

Swapnil Sayan Saha, Shafizur Rahman, Tahera Hossain, 井上創造, Md Atiqur Rahman Ahad

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 1563 - 1570 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

The goal of the Sussex-Huawei Locomotion-Transportation (SHL) recognition challenge is to classify 8 modes of transportation and locomotion activities recorded using a smartphone inertial sensor. In this paper, Team Orion extracts 36 quantitative features per sensor (totalling 226 features) of the dataset provided in the SHL recognition challenge and provides a processing pipeline for training the classifiers embracing parallel computation and out-of-memory processing. One-vs-one quadratic Support Vector Machine (1-1 QSVM) and Bagged Decision Trees with 45 learners (EoC-45) were used for classification of the DU Mobility Dataset. The same features/pipeline provided 91% and 92% classification accuracies respectively on the SHL recognition challenge dataset. Using one-vs-one cubic Support Vector Machine (1-1 CSVM) on SHL, we received the highest classification accuracy of 92.8%. Afterwards, Artificial Neural Network (ANN) was applied on the dataset and accuracies of 93.6%, 88.18% and 90.05% were obtained for training, testing and validation phases. The results provide promising prospects of supervised and neural network classification for locomotion analysis.

Kyutacar

その他リンク： https://dl.acm.org/citation.cfm?id=3267524

Study of LoRaWAN Technology for Activity Recognition 査読有り

Tahera Hossain, 土井祐介, Tahia Tazin, Md Atiqur Rahman Ahad, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 5 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

In this paper, we explore LoRaWAN (Long Range Wide
Area Network) sensor for human activity recognition. In
this research, we want to verify activity recognition by
using LoRaWAN devices. We want to explore relation
between packet loss and activity recognition accuracy
from LoRaWAN sensor data. Afterwards, we study
LoRaWAN sensors data transfer ability in a real
caregiving center. We want to estimate the packet loss
amount from realistic sensors. In LoRaWAN technology,
the amount of sensor nodes connected with a single
gateway have an impact on the performance of sensors
ultimate data sending capability in terms of packet loss.
By exploring a single gateway, we transfer the
LoRaWAN sensor data to the cloud platform
successfully. We evaluate LoRaWAN accelerometer
sensors data for human activity recognition. We explore
the Linear Discriminant Analysis (LDA), Random Forest
(RnF) and K-Nearest Neighbor (KNN) for classification.
We achieve recognition accuracy of 94.44% by LDA,
84.72% by RnF and 98.61% by KNN. Then we simulate
the packet loss environment in our dataset to explore
the relation between packet loss and accuracy. In real
caregiving center, we did experiment with 42 LoRaWAN
sensors node connectivity and data transfer ability to
evaluate the packet received and packet loss
performance with LoRaWAN sensors.

Kyutacar

その他リンク： http://hasca2018.hasc.jp/

MEASURed: A Multi-Sensor Setting Activity Recognition Simulation Tool 査読有り

武田紳吾, Paula Lago, 大北剛, 井上創造

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 5 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

Motion capture generates data which are often more accurate
than those captured by multiple of accelerometer
sensors by their physical specification. Based on the observation
that accelerometer data can be virtually build by
the second derivation of position data from motion capture,
we propose a simulator, called MEASURed, for activity
recognition classifier. MEASURed can accommodate
any number of virtual accelerometer sensors on the
body based on some given motion capture data. Therefore,
MEASURed can evaluate activity recognition classifiers in
settings with different number, placement, and sampling
rate of accelerometer sensors. Our results show that the
F1-Score estimated by MEASURed is close to that obtained
with the real accelerometer data.

Kyutacar

その他リンク： http://hasca2018.hasc.jp/

FonLog - A Mobile App for Nursing Activity Recognition 査読有り

Nattaya Mairittha (Fah), Tittaya Marittha (Fon), 井上創造

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Demo 4 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

We propose FonLog: a mobile app that can be used for a
data collection tool in human activity recognition for nursing
services. The app has essential features to collect activity
data efficiently found by the feedbacks from nursing facilities
from the staffs, namely, recording activity targets, a
user-friendly interface, recognition feedback, customizable
detailed records, instant activity, and offline functionality.

Kyutacar

その他リンク： http://ubicomp.org/ubicomp2018/

Sensing Experiment in a Caregiving Facility for Correlation Analysis of Sleep and Daytime Activities 査読有り

松木萌, 井上創造

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 4 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

We present that we get experiment for 5 months with 30 resident of a caregiving facility to collect big data and toanalyze of the correlation between sleep and daytime behavior. Analysis of sleep is useful for health care and selfanalysis. However, the exist sleep analysis application does not analyze correlation between sleep and the daytime activities such as what kind of activity affect from sleep, and what kind of activity should be taken to improve sleep quality. That is analysis of correlation between sleep and activities is important but it icollectins difficult to collect both the daytime activities data like "meal" and "toilet" and sleep data over a long period of time . In this paper, we get sensing experiment at the caregiving facility to collect big data for 30 subjects and for 5 months. Furthermore, by collecting care records for subject, it is possible to collect the day-
time activities data. Finally, we analyze the data of five subjects for 26 days, it was found that (1) the sleeping situation can estimate whether users will do daytime exercise is performed with an accuracy of 91% at the maximum (2) It was found that the information of the daytime exercise influences the time which user start of sleep.

Kyutacar

その他リンク： http://ubicomp.org/ubicomp2018/

Activity Recognition by Using LoRaWAN Sensor 査読有り

Tahera Hossain, Tahia Tazin, Md Atiqur Rahman Ahad, 井上創造

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 4 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

Low Power Wide Area (LPWA) technologies are
monumental for the IoT sector. Among the LPWA
technologies, long range (LoRa) and narrowband (NB)-
IoT are two promising technologies. In this paper, we
explore LoRaWAN (LoRa Wide Area Network) sensor for
human activity recognition. To support the ageing

population in the world, assisted living and sensor-
based human activity recognition are important

research areas. In this research, we propose an activity
recognition framework by exploiting LoRaWAN sensor
and its accelerometer data. In our framework, we
explore Arduino Uno, Arduino Lucky Shield having a
number of different sensors, and LoRaWAN to build one
compact system. By exploring a LoRaWAN Gateway, we
transfer the sensor data to SORACOM cloud platform
successfully. Then from the cloud data, a few statistical
features are computed to classify three activities such
as walk, stay and run. We aggregate the time series
data into different action labels that summarize the
user activity over a time interval. After, we train data
to induce a predictive model for activity recognition. We
explore the K-Nearest Neighbor (KNN) and Linear
Discriminant Analysis (LDA) for classification. We
achieve recognition accuracy 80% by KNN and 73.3%
by LDA. The result provides promising prospect for
LoRaWAN sensor for improving healthcare monitoring
service.

Kyutacar

その他リンク： http://ubicomp.org/ubicomp2018/

Improving Sensor-based Activity Recognition Using Motion Capture as Additional Information 査読有り

Paula Lago, 武田紳吾, 大北剛, 井上創造

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 4 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

We propose a new method for human activity recognition
using a single accelerometer sensor and additional sensors
for training. The performance of inertial sensors for complex

activities drops considerably compared with simple activ-
ities due to inter-class similarities. In such cases deploy-
ing more sensors may improve the performance. But such

strategy is often not feasible in reality due to costs or pri-
vacy concerns among others. In this context, we propose

a new method to use additional sensors only in training
phase. We introduce the idea of mapping the test data to
a codebook created from the additional sensor information.
Using the Berkeley MHAD dataset our preliminary results
show this worked positively; improving by 10.0% both the
average F1-score and the average accuracy. Notably, we
achieved an average improvement of 143.1% for the stand,
sit and sit to stand activities, typical activities for which the
inertial sensor is less informative when using the wrist-worn
accelerometer.

Kyutacar

その他リンク： http://ubicomp.org/ubicomp2018/

Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification 査読有り

Tittaya Marittha (Fon), 大北剛, 井上創造

Ubicomp Workshop on Computing For Well-being (WellComp) 4 pages 2018年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Singapore Singapore

Symptoms estimation is important in the diagnosis of diseases. Pay attention to methods of assessing symptoms and collecting data on multiple symptoms that are keys to significantly enhance the effectiveness of the diagnosis, in addition, to make more informed decisions for both patients and doctors.
In this paper, we deal with symptoms estimation using the Twitter data, focusing on a diabetic retinopathy disease, to denote each answer as a "Yes" answer or a "No" answer. We propose a Long Short-Term Memory (LSTM) to show that the proposed method is effective.

Kyutacar

その他リンク： http://wellcomp.org

介護施設紹介コールセンター記録のアンサンブル学習による将来予測と傾向分析査読有り

松木萌, 井上創造, 清田陽司

情報処理学会論文誌 2018年07月

記述言語：日本語掲載種別：研究論文（国際会議プロシーディングス）

介護施設紹介コールセンターの記録データをアンサンブル学習を用いて傾向分析や将来予測を行い，「コールセンター」「介護施設」「相談者と入居者」の三者にとって有用な知見を取得する．介護分野における問題に対して，現場のデータを分析し問題解決に有用な知見を得る研究は多くあるが，それらは入居後の問題解決に向けたデータ分析がほとんどである．本研究では，介護施設入居前の分析も重要と考え，入居前の相談を受け付けるコールセンターの記録データを分析する．分析方法は，アンサンブル学習を用いて，説明変数の属性値を2値化し，属性の重要度と目的変数に対する正負の相関を同時に可視化した．記録データは，相談者1名に対し1行，「性別」や「介護度」のような属性を列とした，7,685行106列の行列データである．分析の結果，記録に欠損が多い人は成約に行かないことや，交通手段が見学に行くかどうかの重要な要因であること，「見学するかどうか」は機械学習による精度が96．8%であること，入居決定の決め手は「介護サービス」ではなく，「きれいさ」や「印象」，「距離」であることなど，10件ほどの知見を取得した．

Kyutacar

Virtual Realty Implementation of Steering Hands Motion in Driving Simulator with Unity Technology 査読有り

生駒哲一, 土井祐介, 井上創造

International Conference on Informatics, Electronics & Vision (ICIEV) & 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR) 6 pages 2018年06月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Kitakyushu Kitakyushu

Abstract―Motivated to achieve visual feedback of body motion
in head mounted virtual reality, proposal of this paper is one
practical implementation method of a system that captures hands
motion of car driver in steering operation via vision sensor and
displays the driver’s hands over virtual reality graphics governed
by Unity technology. It utilizes TCP/IP socket communication
with client/server framework for management of passing data

among multiple computer as clients. Actual implementation re-
sult has been reported under driving simulator facility equipped

with two-axes motion actuators and HTC Vive head mounted
display for virtual reality based on Unity technology as graphics
and driving simulator software engine.

A Study on Sensor-based Activity Recognition Having Missing Data 査読有り

Tahera Hossain, 後藤広樹, Md Atiqur Rahman Ahad, 井上創造

International Conference on Informatics, Electronics & Vision (ICIEV) & 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR) 6 pages 2018年06月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Kitakyushu Kitakyushu

Abstract― Human activity recognition is an important area for
various applications. Sensor-based activity recognition
deteriorates while partial data are lost. Hence, in this paper,
we study activity recognition in the presence of data loss.
Earlier, we explored sensor-based activity recognition where
we train the data with randomly missed data [1]. It is required
to investigate better features for handling missing data. Here,
we evaluate activity performance result with missing data
environment with various feature combinations for multiple
classifiers. Initially, we developed a simulated environment to
study the impact of features. Afterward, we evaluated our
proposed feature-based method on a benchmark dataset
named HASC dataset. The dataset has no missing data.
However, to evaluate our approach, we added various levels of
missing data randomly and studied the performances. We
explored mean, variance, skewness and kurtosis as statistical
features based on a time-windowing approach. For
classification study, we exploited two classifiers called Nave
Bayes and Random Forest. Our approach and study
demonstrated satisfactory recognition results under various
feature combinations in different situations of missing data.

Machine Learning of User Attentions in Sensor Data Visualization 査読有り

藤野慶汰, 井上創造, 柴田智広

EAI International Conference on Mobile Computing, Applications and Services (MobiCASE) 125 - 143 2018年03月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

In this paper, we propose a method to automatically esti- mate important points of large sensor data by collecting users attention points when visualized, and by applying supervised machine learning al- gorithm. For large scale sensor data, it is difficult to find important points just by visualization, because the points are buried in a large scope of visualization. We show the result of the estimation, where the accuracy was over 80% for multiple visualization. We also show the result of re- usability for new type of visualization, which performed still 70-80% of accuracies.

その他リンク： http://mobicase.org/2018/show/home

Dialogue Breakdown Detection with Long Short Term Memory 査読有り

Tittaya Marittha (Fon), 大北剛, 井上創造

EAI International Conference on Mobile Computing, Applications and Services (MobiCASE) poster 245 - 250 2018年03月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

This paper aims to detect the utterance which can be categorized as the breakdown of the dialogue flow. We propose a logistic regression-based and a Long Short-Term Memory (LSTM)-based methods. Using the input with utterance-response pairs the performance of the LSTM-based method is superior to that of the logistic regression-based method in 36% measured with F-measure. We also measured the performance using the performance with utterance-response pairs: the performance with the input only with responses is unexpectedly inferior to those with responses in 6% to 23% measured with F-measure.

その他リンク： http://mobicase.org/2018/show/home

Gamification for High-quality Dataset in Mobile Activity Recognition 査読有り

Nattaya Mairittha (Fah), 井上創造

EAI International Conference on Mobile Computing, Applications and Services (MobiCASE) poster 216 - 222 2018年03月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

This paper presents a gamification concept for getting high- quality user-annotated datasets in the context of mobile activity recogni- tion. The‘novel’idea behind this concept is that users are motivated by getting feedback about the quality of their labeling activity as rewards or gamification element. For that, the collected sensor data and labels are used as training data for a machine learning algorithm for determining the dataset quality based on the resulting accuracy. By using the pro- posed method, the results show that the gamification elements increase the quantity (the proposed method is greater than the naive by at least 305) and‘ quality ’(the accuracy of the proposed data outperformed the original data by at least 4.3%) of the labels. Besides, the cheating de- tection algorithm could detect cheating with the accuracy of more than 70% that is fascinating work.

その他リンク： http://mobicase.org/2018/show/home

Improving Activity Recognition for Missing Data 査読有り

Tahera Hossain, 後藤広樹, 井上創造

EAI International Conference on Mobile Computing, Applications and Services (MobiCASE) Student Workshop 4 pages 2018年02月

Towards pervasive geospatial affect perception 査読有り

Raja M., Exler A., Hemminki S., Konomi S., Sigg S., Inoue S.

GeoInformatica 22 ( 1 ) 143 - 169 2018年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

© 2017, Springer Science+Business Media New York. Due to the enormous penetration of connected computing devices with diverse sensing and localization capabilities, a good fraction of an individual’s activities, locations, and social connections can be sensed and spatially pinpointed. We see significant potential to advance the field of personal activity sensing and tracking beyond its current state of simple activities, at the same time linking activities geospatially. We investigate the detection of sentiment from environmental, on-body and smartphone sensors and propose an affect map as an interface to accumulate and interpret data about emotion and mood from diverse set of sensing sources. In this paper, we first survey existing work on affect sensing and geospatial systems, before presenting a taxonomy of large-scale affect sensing. We discuss model relationships among human emotions and geo-spaces using networks, apply clustering algorithms to the networks and visualize clusters on a map considering space, time and mobility. For the recognition of emotion and mood, we report from two studies exploiting environmental and on-body sensors. Thereafter, we propose a framework for large-scale affect sensing and discuss challenges and open issues for future work.

DOI： 10.1007/s10707-017-0294-1

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85014904338&origin=inward

Deep Recurrent Neural Network for Mobile Human Activity Recognition with High Throughput 査読有り

井上聖也, 井上創造, 西田健

Journal of Artificial Life and Robotics 1 - 13 2017年12月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, we propose a method of human activity recognition with high throughput from raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate various architectures and its combination to find the best parameter values. The “high throughput” refers to short time at a time of recognition. We investigated various parameters and architectures of the DRNN by using the training dataset of 432 trials with 6 activity classes from 7 people. The maximum recognition rate was 95.42% and 83.43% against the test data of 108 segmented trials each of which has single activity class and 18 multiple sequential trials, respectively. Here, the maximum recognition rates by traditional methods were 71.65% and 54.97% for each. In addition, the efficiency of the found parameters was evaluated using additional dataset. Further, as for throughput of the recognition per unit time, the constructed DRNN was requiring only 1.347 ms, while the best traditional method required 11.031 ms which includes 11.027 ms for feature calculation. These advantages are caused by the compact and small architecture of the constructed real time oriented DRNN.

その他リンク： https://doi.org/10.1007/s10015-017-0422-x

Recognition of Multiple Overlapping Activities Using Compositional CNN-LSTM Model 査読有り

大北剛, 井上創造

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 2017年09月

Quality Requirements for Electronic Health Record Systems A Japanese-German Information Management Perspective 査読有り

A. Winter, K. Takabayashi, F. Jahn, Eizen Kimura, R. Engelbrecht, R. Haux, M. Honda, U. H. Hubner, 井上創造, C. D. Kohl, T. Matsumoto, Y. Matsumura, K. Miyo, 中島直樹, H. -U. Prokosch, M. Staemmler

Journal of Methods of Information in Medicine 56 92 - 104 2017年09月

記述言語：英語掲載種別：研究論文（学術雑誌）

Background: For more than 30 years, there has been close cooperation between Japanese and German scientists with regard to information systems in health care. Collaboration has been formalized by an agreement between the respective scientific associations. Following this agreement, two joint workshops took place to explore the similarities and differences of electronic health record systems (EHRS) against the background of the two national healthcare systems that share many commonalities. Objectives: To establish a framework and requirements for the quality of EHRS that may also serve as a basis for comparing different EHRS. Methods: Donabedian’s three dimensions of quality of medical care were adapted to the outcome, process, and structural quality of EHRS and their management. These quality dimensions were proposed before the first workshop of EHRS experts and enriched during the discussions. Results: The Quality Requirements Framework of EHRS (QRF-EHRS) was defined and complemented by requirements for high quality EHRS. The framework integrates three quality dimensions (outcome, process, and structural quality), three layers of information systems (processes and data, applications, and physical tools) and three dimensions of information management (strategic, tactical, and operational information management). Conclusions: Describing and comparing the quality of EHRS is in fact a multidimensional problem as given by the QRF-EHRS framework. This framework will be utilized to compare Japanese and German EHRS, notably those that were presented at the second workshop.

Kyutacar

その他リンク： https://doi.org/10.3414/ME17-05-0002

介護サービス向上に向けた介護事故事例テキストの分析(Text Analysis of Incident Reports for Preventing Accidents in Caregiving}) 査読有り

峯崎智裕, 松木萌, 井上創造

情報処理学会論文誌 58 ( 10 ) 2017年07月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文は，複数介護施設における事故報告書を使用して，テキストマイニングおよび機械学習により事故の起こりうる状況を分析した結果について述べる．

まず，テキストデータと多変量データが混合したデータに対して，テキストマイニングおよびランダムフォレスト法を組み合わせて，事故の結果に対して影響する要因を抽出する方法を提案した．

まずテキストデータについては分かち書きを行い単語文書行列を構成し，単語についてクラスタリングを行った結果を元の多変量データと結合し，事故の結果として目的変数を設定しランダムフォレスト法￥new{を2段階で適用しながら重要な単語クラスタ及び重要な単語と属性}を抽出し，決定木によって可視化するという手法である．

この手法を，介護施設から得られた5,189件の事故事例について適用したところ，

原因不明のあざの発見のされ方や，転倒・ずり落ちから打撲につながるような行動，誤嚥につながる状況，無断外出につながる行動といった幾つかのパターンを抽出できた．

Kyutacar

センサーと医療ビッグデータを活用した医療サービス分析システムの研究開発—業務分析から課題を抽出し改善につなげる

杉山康彦, 白水麻子, 中島直樹, 井上創造

看護管理 ( 看護管理 ) 27 ( 8 ) 658 - 667 2017年06月

携帯センサと近接センサを用いた看護師業務分析査読有り

磯田達也, 井上創造, 花沢明俊, 野原康伸, 白水麻子, 杉山康彦, 平田真理, 町田京子, 中島直樹

情報処理学会論文誌 57 ( 10 ) 2197 - 2209 2017年01月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本研究では,看護師の業務分析のため,33 日間に渡り看護師の業務行動データを収集する実験を行い,業務中の看護師の行動の激しさおよび,業務時間に影響を与える要因について分析を行った.データ収集実験では,38 人の看護師を被験者に設定して,装着型の小型センサ端末を装着した状態で業務を行ってもらい,加速度データおよび看護師間の対面情報,看護師業務情報を収集した.また,赤外線を用いた情報通信機器によって看護師の位置情報も同時に収集した.本稿では,看護師業務中の行動の激しさを目的変数,看護師業務毎の回数,対面回数,場所毎の訪問回数などを説明変数に設定して,決定木 (回帰木) を用いた要因分析を行った.その結果,他の看護師との対面回数が多く,病室に何度も訪れている看護師や,リハビリ介助業務や行動介助業務などの患者の介助に関わる業務を行う看護師ほど,行動の激しさが大きくなるという結果を得た.また,業務時間が業務効率に直結していると考え,各業務時間の長さに影響を及ぼす要因について回帰分析によって調べた.その後,単回帰分析により有意水準 5%で有意となった説明変数の業務だけを抽出し,その業務に対して決定木を用いた要因分析を行った.単回帰分析の結果, 14 の業務において有意な結果が得られた.また,決定木による要因分析の結果,ほとんどの業務において他の看護師との対面人数が業務時間に影響を与えていることがわかった.また,食事介助業務中に特定の場所に訪れる看護師ほど業務時間が長くなるという結果を得た.

Kyutacar

ウェアラブルセンサを用いたヒューマンセンシング

井上創造

日本知能情報ファジィ学会誌 ( 日本知能情報ファジィ学会誌 ) 170 - 186 2017年01月

Recognizing and Understanding Nursing Activities for a Whole Day with a Big Dataset 査読有り

井上創造, 上田修功, 野原康伸, 中島直樹

Journal of Information Processing 24 ( 6 ) 853 - 866 2017年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, we provide a real nursing data set for mobile activity recognition that can be used for supervised machine learning, and big data combined the patient medical records and sensors attempted for 2 years, and also propose a method for recognizing activities for a whole day utilizing prior knowledge about the activity segments in a day. Fur- thermore, we demonstrate data mining by applying our method to the bigger data with additional hospital data. In the proposed method, we 1) convert a set of segment timestamps into a prior probability of the activity segment by exploit- ing the concept of importance sampling, 2) obtain the likelihood of traditional recognition methods for each local time window within the segment range, and, 3) apply Bayesian estimation by marginalizing the conditional probability of estimating the activities for the segment samples. By evaluating with the dataset, the proposed method outperformed the traditional method without using the prior knowledge by 25.81% at maximum by balanced classification rate, and outperformed by 6.5% the F-measure with accepting 1 hour of margins. Moreover, the proposed method significantly reduces duration errors of activity segments from 324.2 seconds of the traditional method to 74.6 seconds at maximum. We also demonstrate the data mining by applying our method to bigger data in a hospital.

Kyutacar

集会報告　マルチメディア，分散，協調とモバイル（DICOMO2017）シンポジウム

井上創造, 松木萌, 岡崎有彩, 清田陽司

情報管理 ( 国立研究開発法人科学技術振興機構 ) 60 ( 8 ) 603 - 607 2017年01月

Supervised and Unsupervised Transfer Learning for Activity Recognition from Simple In-home Sensors 査読有り

井上創造, 潘新程

International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) (Acceptance Rate: 30%) 20 - 27 2016年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Hiroshima Hiroshima

In this paper, we propose an approach to improve the accuracy of life activity estimation using device-free sensors in the home.

We assumed two scenarios in which we only have training data from other households with labels and we also have training labels for our own household and, proposed the method to compose supervised transfer between labeled data and unsupervised for each scenario.

We developed the system which consists of an smartphone apps and web server, and gathered subjects from open called households during a period of approximately four months, and obtained approximately 11,745 activity inputs, 7.14GB of sensor data, and power consumption data of 237,280 hours from 35 households, and found to outperform naive methods in the both scenarios.

Kyutacar

その他リンク： http://dl.acm.org/citation.cfm?doid=2994374.2994400

Mobile Activity Recognition from Training Labels with Inaccurate Activity Segments (Best paper candidate) 査読有り

戸田隆道, 井上創造, 上田修功

International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) (Acceptance Rate: 30%) 57 - 64 2016年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Hiroshima Hiroshima

In this paper, we propose an approach to improve mobile activity recognition given training dataset with inaccurate segments, in which the beginning and the ending timestamps of homogeneous and continuous activities have inaccurate boundaries by human errors.

In the proposed approach, we A) convert the training dataset to multi-label samples, B) train the dataset with multi-label EM learning algorithm, and C) apply a segmentation method using not only the estimated labels, but also the original segment information.

We evaluate the proposed approach for 3 datasets including simulation data and real activity data, 2 machine-learning algorithms, and various inaccuracies, and show that the proposed approach outperformed the naive methods for the questions of Q1) fixing the segments of the training data and Q2) improving the recognition accuracy by cross validation.

Kyutacar

その他リンク： http://dl.acm.org/citation.cfm?doid=2994374.2994400

Activity recognition and future prediction in hospitals 査読有り

Inoue S.

ACM International Conference Proceeding Series 28-November-2016 59 - 65 2016年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

© 2016 ACM. In this paper, we firstly introduce our work [9] where we proposed for recognizing whole day activities using prior knowledge, and applied the method for real nursing sensor dataset we have collected. Then, we introduce the method for predicting the near future of nurses by integrating nurse activity data, location data, and medical records, based on our work [10] . For both works, we independently collected real and open nursing datasets with 2 weeks of accelerometers and training labels from 22 nurses for the former work, and nurse activity, location, medical payment, and nursing need data from 35 nurses and 96 patients for 40 days for the latter work.

DOI： 10.1145/3004010.3004012

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85008187825&origin=inward

機械学習で怖い「次元の呪い」手法の選択は適材適所で

井上創造

まるわかり！人工知能最前線：日経コンピュータ ( まるわかり！人工知能最前線：日経コンピュータ ) 98 - 193 2016年10月

Predicting Daily Nursing Load from Nurses’ Activity Logs and Patients’ Medical Records 査読有り

井上創造, 磯田達也, 白水麻子, 杉山康彦, 野原康伸, 中島直樹

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 4 pages 2016年09月

Recognizing Unknown Activities Using Semantic Word Vectors and Twitter Timestamps 査読有り

松木萌, 井上創造

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 823 - 830 2016年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Heidelberg, Germany Heidelberg, Germany

In this paper, we propose a method for activity recognition, which can estimate new activities which does not appear

in the training data, combining word vectors constructed from semantic word vectors and Twitter timestamps. Be- cause traditional activity recognition utilizes supervised machine learning, unknown activity classes which do not appear in the training dataset is unable to be estimated. For this problem, zero-shot machine learning method is pro- posed, but it requires the preparation of semantic codes.

As semantic codes, we utilize word vectors constructed from semantic word vectors and Twitter timestamps. To evaluate the proposed method, we evaluated whether we could estimate unknown activity classes, with the sensor data set collected from 20 households for 4 months, along with the user-generated labels using the web system which can estimate, modify, and add new activity types. As a re- sult, the proposed method could even estimate unknown activity classes. Moreover, by utilizing Twitter timestamps and semantic word vectors from the Japanese Wikipedia in word vectors, the method could estimate 9 unknown activity classes.

Kyutacar

その他リンク： http://hasca2016.hasc.jp

機械学習をIoTに応用人間の行動を認識・予測する

井上創造

日経コンピュータ ( 日経コンピュータ ) 78 - 81 2016年09月

機械学習をIoTに応用、人間の行動を認識・予測する

井上創造

日経ITPro ( 日経ITPro ) 2016年08月

機械学習で怖い「次元の呪い」手法の選択は適材適所で

井上創造

日経コンピュータ ( 日経コンピュータ ) 86 - 89 2016年08月

あなたの仕事を劇的に効率化！機械学習のインパクト第3回機械学習で怖い「次元の呪い」、手法の選択は適材適所で

井上創造

日経ITPro ( 日経ITPro ) 2016年08月

ウェアラブルセンサを用いたヒューマンセンシング

井上創造

知能と情報 28 ( 6 ) 170 - 186 2016年01月

Nursing Activity Sensing Using Mobile Sensors and Proximity Sensors 査読有り

磯田達也, 野原康伸, 井上創造, 白水麻子, 杉山康彦, 平田真理, 町田京子, 中島直樹

The 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS) 7 pages 2015年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Hawaii, USA. Hawaii, USA.

In recent years, big data are utilized in many indus- tries. In this study, in order to analyze duties of the nurses, we performed experiments to collect the du- ties activity data of the nurses for a long term. We set 38 nurses as subjects and asked them to carry out duties while attaching a wearable small sensor device, and collected the acceleration data, meeting informa- tion between nurses and the nurse duties information. In addition, we collected the location information of the nurses by using infrared information and communi- cation equipment at the same time. From various data collected, we analyzed intensity and positional informa- tion of duties activity of the nurse, meeting information and the duties information between nurses and consid- ered the influence that each factor affected to the nurse. As the result, we found that intensity of the activity in- creases in such nurses as who has many times of meeting with other nurses, visits the patient room many times, or who works on jobs concerning with the assistance of the patients such as rehabilitation assistance duties or the activity assistance duties.

Kyutacar

その他リンク： http://sci-sss.org/sss2015/

A Personalized Load Forecasting Enhanced by Activity Information 査読有り

Yong Ding, 井上創造, Martin Alexander Neumann, Erwin Stamm, 潘新程, Michael Beigl

IEEE International Smart Cities Conference (ISC2-2015) 153 - 158 2015年10月

Experiment for Automatic Assessment of User-generated Tests 査読有り

谷口敦, 井上創造

IEEE International Conference on MOOCs, Innovation and Technology in Education (MITE) 152 - 155 2015年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Amiritsar, India Amiritsar, India

In this paper, we propose the e-Learning web system

in which any users can make questions. We also show an

algorithm to assess the answer logs in consideration of difficulty

and validity of questions. Today, education systems such as eLearning

are adopted in many universities, but only teachers

or a limited number of people can make questions in many

scenes so that they bear a great burden of making questions.

Therefore it is possible to reduce the burden on teacher if any

users can make questions. We formulated algorithm to reflect

difficulty and validity of the questions to evaluation and made

Web system to make questions and answer them. We carried

out an experiment in a class of the university whether it would

be possible to make a correct evaluation on real human-made

questions using the system by algorithm of suggestion technique.

As a result, assessment results in consideration of difficulty and

validity were calculated for the human-made questions.

その他リンク： http://www.mite2015.com

Experiment for Nursing Activity Analysis Using Mobile Sensors and Proximity Sensors 査読有り

磯田達也, 野原康伸, 井上創造, 白水麻子, 杉山康彦, 平田真理, 町田京子, 中島直樹

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 153 - 156 2015年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

In this study,in order to analyze duties of the nurses,we performed experiments to collect the duties activity data of the nurses for a long term.We set 38 nurses as subjects and asked them to carry out duties while attaching a wearable small sensor device,and collected the acceleration data,meeting information between nurses and the nurse duties information.In addition,we collected the location information of the nurses by using infrared information and communication equipment at the same time.In fact,we were able to extract a total of 1,805,760 pieces of activity rhythm of nurses,462,418 pieces of location information data,459,139 pieces of meeting information data,and 12,406 pieces of nurse duties information.In the future,we will visualize the nurse’s activities,and analyse the factors that affect the activity rhythm,the nurse duties,and the location information.

DOI： 10.1145/2800835.2800901

Kyutacar

Scopus

その他リンク： http://ubicomp.org/ubicomp2015/

A Method for Automatic Assessment of User-generated Tests and Its Evaluation 査読有り

谷口敦, 井上創造

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 225 - 228 2015年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

In this paper, we propose the e-Learning web system in which any users can not only answer questions, but also make questions. We also show an algorithm to assess the answer logs in consideration of difficulty and validity of questions. Today, education systems such as e-Learning are adopted in many universities, but only teachers or a limited number of people can make questions in many scenes so that they bear a great burden of making questions. Therefore it is possible to reduce the burden on teacher if any users can make questions. We formulated algorithm to reflect difficulty and validity of the questions to evaluation and made Web system to make questions and answer them. We carried out an experiment in a class of the university whether it would be possible to make a correct evaluation on real human-made questions using the system by algorithm of suggestion technique. As a result, assessment results in consideration of difficulty and validity were calculated for the human-made questions.

Kyutacar

その他リンク： http://ubicomp.org/ubicomp2015/

Analyzing Daily-life Activities and Power Consumptions Using Tablet Sensors and Activity Annotation Web System 査読有り

潘新程, 峯崎智裕, 磯田達也, 田中翔太, 内野百里, 井上創造

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 1443 - 1452 2015年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

This paper describes the result of concrete analysis of cor- relation between in-house activities and power consump- tions that has been conducted in order to reduce the home power consumption. Recently, various studies on power consumptions are conducted. In this study, we have exe- cuted system development, experiments by subjects, analy- sis of correlation between life-pattern and power consump- tions and proposal of electrical power reduction for the pur- pose of reducing home power consumption. A present, we are working on analysis of correlation between a life pat- tern and electrical power consumption of the residents. We asked the residents for inputting their activities for around several minutes per day using a system that we have de- veloped. We were able to collect approximately 11,745 activity inputs, approximately 7.14GB of sensor data, and power consumption data of 237,280 hours corresponding to about 4 months from 35 homes. Using the collected data, we carried out the multiple regression analysis taking an es- timated time of activity and sustained period as explanation variables and average power consumption per day as an objective variable. As the result, it was known that there is correlation between life-pattern and power consumption. In this paper, we will show that it becomes possible to execute concrete analysis of relationship between power consump- tion and activities of residents by using the label data of resident’s life pattern.

DOI： 10.1145/2800835.2801615

Kyutacar

Scopus

その他リンク： http://hasca2015.hasc.jp/

いよいよ本気でユビキタスヘルスケア

井上創造, 中島直樹

情報処理学会誌 ( 情報処理学会誌 ) 56 ( 9 ) 870 - 873 2015年09月

Predictive Approaches for Low-cost Preventive Medicine Program in Developing Countries 査読有り

Yukino Baba, Hisashi Kashima, 野原康伸, 甲斐瑛子, Partha Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, 井上創造, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, 上田修功, 喜連川優, 中島直樹

The 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2015年08月

ウェルネスのためのICT：0．編集にあたって

井上創造, 村上知子

情報処理学会誌 ( 情報処理学会誌 ) 56 ( 2 ) 132 - 133 2015年01月

Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study 査読有り

野原康伸, 甲斐瑛子, Partha Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, 井上創造, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Yukino Baba, Hisashi Kashima, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, 上田修功, 喜連川優, 中島直樹

J Med Internet Res 16 2014年12月

Evolving Health Consultancy by Predictive Caravan Health Sensing in Developing Countries 査読有り

甲斐瑛子, Ashir Ahmed, 井上創造, 中島直樹, 喜連川優

ACM UbiComp International Workshop on Smart Health Systems and Applications (SmartHealthSys) 1225 - 1232 2014年09月

Room Exit Recognition Using Mobile Accelerometers and Illuminometers 査読有り

磯田達也, 井上創造, 忽那秀治, 河野正人

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 731 - 735 2014年09月

Training Human Activity Recognition for Labels with Inaccurate Time Stamps 査読有り

戸田隆道, 井上創造, 田中翔太, 上田修功

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 863 - 872 2014年09月

A Method for Tracking On-body Sensor Positions Utilizing Prior Knowledge 査読有り

右田尚人, 弓山卓哉, 井上創造, 西田健

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 758 - 766 2014年09月

A Method for Assessing User-generated Tests for Online Courses Exploiting Crowdsourcing Concept 査読有り

Ghada Farouk Naiem, 井上創造

International Workshop on Web Intelligence and Smart Sensing (IWWISS) 2014年09月

Applicability of Portable Health Clinic for ageing Society 査読有り

Ashir Ahmed, Andrew Robeiro-Hargrave, Rafiqul Islam Maruf, 井上創造, 中島直樹

International Conference on Human-Computer Interaction (HCI International), Springer LNCS 2014年06月

Empowering the healthcare worker using the Portable Health Clinic 査読有り

甲斐瑛子, Andrew Robeiro-Hargrave, 井上創造, 野原康伸, Rafiqul Islam Maruf, 中島直樹, Ashir Ahmed

The 28th IEEE International Conference on Advanced Information Networking and Applications (AINA) 759 - 764 2014年05月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Victoria, Canada Victoria, Canada

We present a remote healthcare consultancy system that enables healthcare workers to identify noncommunicable diseases in unreached communities. The healthcare system combines medical sensors with mobile health and is called a Portable Health Clinic. The Portable Health Clinic fits into a briefcase and is operated by the healthcare worker. The goal of this research is empower the healthcare worker further by allowing her to recognize spurious measurements and to make lifestyle recommendations. In this paper, we show how to process the data: combine, link and compare captured in patient electronic health records stored in database. We applied association rule technique to find common set of rules in order to build a clinical decision support system. We also showed examples of the meaningful information from the analyzed data to build a better clinical decision support.

DOI： 10.1109/AINA.2014.108

Scopus

その他リンク： http://www.aina-conference.org/2014/

State estimation and control of a mobile robot using Kalman filter and particle filter 査読有り

西田健, 井上創造, 相良慎一

Proc. International Symposium on Artificial Life and Robotics 633 - 636 2014年01月

Toward Measuring Fatigue by Acceleration Data in a Marathon 査読有り

戸田隆道, 井上創造

2013 International Workshop on ICT 4 pages 2013年12月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Beppu Beppu

In this paper, we propose an experimental method which quantifies the degree of fatigue by using acceler- ation sensor data, which could be used to for the system in which users can cheer marathon runners from anywhere by sharing the information of fatigue. We extract features from time windows, apply clustering to classify the types of movement of the runner, and quantified the histogram of them. Using the real marathon data by our subjects, we show the appropriateness of the analysis.

Kyutacar

その他リンク： https://www.ipsj-kyushu.jp/page/ronbun/kouenkai/1002/

State estimation of mobile robot using GPS signal that includes reflected and diffracted waves 査読有り

西田健, 井上創造, 相良慎一

Artificial Life and Robotics 18 ( 3 ) 178 - 186 2013年12月

記述言語：英語掲載種別：研究論文（学術雑誌）

We propose a method to improve the state estimation accuracy of mobile robots placed near high-rise buildings using the statistical property of the reflected and diffracted waves of global positioning system (GPS) signals. First, it is assumed that a GPS signal that contains a reflected and diffracted wave is denoted by the sum of the true position information and noise that follows a time-varying Gaussian distribution. On the basis of this assumption, the time-varying bias of a GPS signal is tracked using a Kalman filter. In addition, a particle filter, which executes sampling and likelihood evaluation using the estimated bias, is developed. With the proposed method, a GPS signal that contains the rejected noise introduced by the conventional method can be used efficiently, and the state estimation accuracy of the robot in a shadow area of GPS satellite can be improved. Furthermore, a control system for an autonomous mobile robot incorporating the proposed state estimation mechanism is developed, and its effectiveness is evaluated via simulation.

DOI： 10.1007/s10015-013-0115-z

Kyutacar

Scopus

その他リンク： http://link.springer.com/article/10.1007%2Fs10015-013-0115-z

Parallel, Distributed, and Differential Processing System for Human Activity Sensing Flows 査読有り

戸田隆道, 井上創造, 李林

International Workshop on Human Activity Sensing Corpus and its Application (HASCA) at Ubicomp 1 - 1 2013年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Zurich Zurich

In this paper, we propose a parallel distributed processing system for data-analytic project including human activity sensing flows, which manages dependency among data and analytic programs, and re-execute updated programs and dependent programs for updated data/programs. In the system, a data analyzer can specify the dependency and parts for requiring distributed parallel processing using Hadoop Streaming, and they can be processed only for updated and the dependent part, with flexibly selecting parallel or sequential execution on the fly. The specification can also specify repeated execution of a single program with different data, while their dependencies are checked separately at execution. We describe the mathematical model, the system design, the usage, and the experimental result applying to the essential process in human activity sensing.

DOI： 10.1145/2494091.2495990

Kyutacar

Scopus

その他リンク： http://hasca2013.hasc.jp/

An Affordable, Usable and Sustainable Preventive Healthcare System for Unreached People in Bangladesh 査読有り

中島直樹, 野原康伸, Ashir Ahmed, Masahiro Kuroda, 井上創造, Partha Ghosh, Rafiqul Islam Maruf, Tatsuo Hiramatsu, Kunihisa Kobayashi, Toyoshi Inoguchi, 喜連川優

World Congress on Medical and Health Informatics (MedInfo) 105 - 1 2013年08月

Portable Health Clinic Packages for BoP 査読有り

野原康伸, 中島直樹, Ashir Ahmed, Masahiro Kuroda, 井上創造, Partha Ghosh, Rafiqul Islam Maruf, Tatsuo Hiramatsu, Kunihisa Kobayashi, Toyoshi Inoguchi

World Congress on Medical and Health Informatics 126 - 8 2013年08月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Copenhagen, Denmark Copenhagen, Denmark

In a developing county, its health/medical infrastructure has many problems. It is difficult for people in BoP (Base of Pyramid) especially lived in rural area to access a medical service. In this study, we propose a package for Portable Health Clinic (PHC) which provides telemedicine service for people in BoP. The package consists of major diagnostic tools and a tablet PC, and gathers measurements using medical Body Area Network (BAN) wirelessly and automatically. It can categorize patients into four groups depending on the priority of their treatment like a triage, and also sent these results to a doctor in a remote healthcare call center via mo-bile network. The package provides immediate consultation with the doctor over the Skype and doctor gives patients a prescription over the network. The package is easy to carry, easy to use, battery-driven and flexible against poor mobile network, and works even in a rural area. We are introducing the PHC packages in a health checkup program whose target is 15,000 subjects in Bangladesh, one of the BoP countries.

Kyutacar

その他リンク： http://www.medinfo2013.dk/

Capturing Nursing Interactions from Mobile Sensor Data and In-room Sensors

井上創造, 林田興祐, 中村優斗, 野原康伸, 中島直樹

International Conference on Human-Computer Interaction (HCI International), Springer LNCS 8014 280 - 289 2013年07月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Las Vegas, USA Las Vegas, USA

In this paper, we show two approaches for capturing nursing interactions in a hospital: 1) finding nursing intervals from mobile sen- sors with accelerometers and audio on nurses, and 2) recognizing nurses’ entrance to a patient’s room from in-room sensors of bed, loudness, and illuminance sensors. For 1), we firstly detect the nurses’ entrance to the patient’s room by walking detection from accelerometers and noise level on mobile sensors, and detect the interval of interaction between nurses and the patient. For 2), we recognize the nurse’s entrance to the patient’s room with in-room sensors, using separate algorithms between day and night. We developed the algorithms using the sensor data collected in a cardiovascular center in a real hospital for one year. It could be a impor- tant baseline technique to find valuable intervals from long and big data of sensors.

その他リンク： http://www.hcii2013.org/ http://link.springer.com/chapter/10.1007%2F978-3-642-39238-2_31

Portable Health Clinic: A pervasive way to serve the unreached community for preventive healthcare

Ashir Ahmed, 井上創造, 甲斐瑛子, 中島直樹, 野原康伸

International Conference on Human-Computer Interaction (HCI International), Springer LNCS 8028 265 - 274 2013年07月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Las Vegas, USA Las Vegas, USA

One billion people (15% of the world population) are unreached in terms of accessing to quality healthcare service. Insufficient healthcare facilities and unavailability of medical experts in rural areas are the two major reasons that kept the people unreached to healthcare services. Recent penetration of mobile phone and the unmet demand to basic healthcare services, remote health consultancy over mobile phone became popular in developing countries. In this paper, we introduce two such representative initiatives from Bangladesh and discuss the technical challenges they face to serve a remote patient. To solve these issues, we have prototyped a portable health clinic box with necessary diagnostic tools, we call it a “portable clinic” and a software tool, “GramHealth” for archiving and searching patients’ past health records. We carried out experiments in three remote villages and in two commercial organizations in Bangladesh by collaborating with local organization to observe the local adoption of the technology. We also monitored the usability of the portable clinic and verified the functionality of “GramHealth”. We display the qualitative analysis of the results obtained from the experiment. GramHealth DB has a unique combination of structured, semi-structured and un-structured data which can be considered as BigData. We have partly analyzed the data manually to find common set of rules to build a better clinical decision support. The model of analyzing the GramHealth BigData is also presented.

DOI： 10.1007/978-3-642-39351-8_29

Scopus

その他リンク： http://www.hcii2013.org/ http://link.springer.com/chapter/10.1007%2F978-3-642-39351-8_29#page-1

「ヘルスケアの現場を支えるIT 」特集号について

山本隆一, 井上創造, 中野美由紀

情報処理学会論文誌デジタルプラクティス ( 情報処理学会論文誌デジタルプラクティス ) 4 ( 3 ) 205 - 206 2013年07月

インタビュー：九州大学中島直樹氏，東京大学山本隆一氏，九州工業大学井上創造氏インタビュー「医療と情報と社会とビッグデータ」

中島直樹, 山本隆一, 井上創造, 中野美由紀

情報処理学会論文誌デジタルプラクティス ( 情報処理学会論文誌デジタルプラクティス ) 4 ( 3 ) 292 - 301 2013年07月

GramHealth BigData for Smart Healthcare Applications 査読有り

甲斐瑛子, 井上創造, Ashir Ahmed

International IEEE Engineering in Medicine and Biology Society (EMBS) Conference 1 page 2013年07月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

We found that remote healthcare consultancy in developing countries archives very unique nature (multi-lingual, multi-modal, multi-media, poly-structured) of personal health records. These types of records are difficult to analyze by the existing data mining tools. We manually analyzed these records and discovered that combining, linking and comparing personal and group records can generate important medical information which can be useful for smart healthcare applications.

Kyutacar

GramHealth: A bottom-up approach to provide preventive healthcare services for unreached community 査読有り

Ashir Ahmed, Lutfe Kabir, 甲斐瑛子, 井上創造

International Conference on IEEE Engineering in Medicine and Biology Society 1 page 2013年07月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Osaka Osaka

Access to healthcare should be as local as possible. However, due to the insufficient healthcare facilities and unavailability of medical experts in rural and disaster areas, more than a billion people in the world remained unreached of quality healthcare services. GramHealth is a software tool designed based on the requirements of unreached community. This paper introduces the requirements and technical challenges of unreached community, describes the concept of GramHealth and displays experimental results obtained from villages in Bangladesh.

DOI： 10.1109/EMBC.2013.6609838

Kyutacar

Scopus

その他リンク： http://embc2013.embs.org/index.html

スマートフォン行動情報収集と看護行動センシング(Smartphone Activity Data Collection and Nursing Activity Sensing)

井上創造

情報処理学会誌 ( 情報処理学会誌 ) 54 ( 6 ) 2013年05月

Finding Nursing in the Room from Accelerometers and Audio on Mobile Sensors 査読有り

中村優斗, 井上創造, 野原康伸, 中島直樹

IUI Workshop on Location Awareness for Mixed and Dual Reality (LAMDa) 17 - 20 2013年03月

Hierarchical Annotation Management Method for Activity Information Collecting System 査読有り

服部祐一, 田中翔太, 井上創造

International Workshop on Network Traffic Control, Analysis and Applications (NTCAA-2012) 662 - 667 2012年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Victoria, Canada Victoria, Canada

Recently, researches for activity recognition with sensor data have been increased by the spread of smart phones with 3-axis accelerometers and gyroscopes. However, collecting various sensor data from many people is difficult. To solve this problem, we developed activity collecting platform using various client software. Moreover, annotating continuous activity data is also an important task. However, this task requires a lot of work by hands. Moreover, an activity has a complex structure, and annotation by human often contains ambiguity. For this reason, a system needs to support work so that a worker may add annotation efficiently and accuracy. Therefore, we propose the annotation software which has the function of hierarchical segmentation and hierarchical annotation.

DOI： 10.1109/BWCCA.2012.115

Scopus

その他リンク： http://www-id.kuma.u-tokai.ac.jp/ntcaa2012/

Sensor Data Analytics to Complement Sparse and Incomplete Medical Records for Diabetes Disease Management 査読有り

Rudy Raymond, 中島直樹, 野原康伸, 井上創造

International Workshop on Pattern Recognition for Healthcare Analytics 5 - 8 2012年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Tsukuba Tsukuba

Diabetes mellitus is considered one of the main chronic diseases, and uncontrolled diabetes can lead to various complications that trigger other chronic dis- eases. Disease management for diabetes is therefore important to reduce the total healthcare cost. Unfor- tunately, managing diabetic patients is often difficult due to their sparse and incomplete medical records. Many patients drop out during treatment, and each pa- tient might require different treatment. On the other hand, the widespread use of mobile devices with var- ious sensors and instant communication capability has enabled healthcare providers to collect and monitor pa- tients’ condition. In this paper, we study the role of sensor data analytics to complement sparse and incom- plete medical records for diabetes disease management. We test various machine-learning techniques on real- world datasets of diabetic patients, and show that sen- sor datasets can be used to improve the precision of methods identifying high-risk patients.

Kyutacar

その他リンク： https://sites.google.com/site/pr4healthanalytics/

Large-scale Sensor Dataset in a Hospital 査読有り

野原康伸, 井上創造, 中島直樹, 上田修功, 喜連川優

International Workshop on Pattern Recognition for Healthcare Analytics 9 - 12 2012年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Tsukuba Tsukuba

In this paper, we describe a sensor dataset, which was collected in a hospital, to be used for pattern recognition and/or data mining for medical purposes. The dataset includes those of patients and nursing care in a cardiovascular center in a hospital. The experi- ment was applied for hospitalized patients who caught such as an acute cardiac infraction or angina (pre- infarction), have been applied PCI (Percutaneous Coro- nary Intervention) or CABG (Coronary Artery Bypass Graft), and have consented to the experiment. The pa- tients provided vital sensor data such as a monitor- ing cardiogram, a bed sensor to measure heart rate and breath, accelerometers, environmental sensors, and also medical information which were recorded in the electronic clinical pathways and indirectly in patients’ sensor data. At the same time, we also gathered ac- celerometer data and RFID data of real nursing in the hospital. As far as we know, these data are one of the ‘biggest data’ of sensors from a real hospital in real sit- uations.

Kyutacar

その他リンク： https://sites.google.com/site/pr4healthanalytics/

Activity Sharing System with Windows Phones and Motion Data

服部祐一, 右田尚人, 田中翔太, 井上創造

Microsoft Research Asia Faculty Summit 1 page 2012年10月

Dependency Management System with Hadoop Streaming for Data-analytic Projects 査読有り

李林, 井上創造

Korea-Japan Joint Workshop on ICT 4 pages 2012年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Pohang, Korea Pohang, Korea

In this paper, we propose a distributed parallel processing system for data-analytic project, which manages dependency among data and analytic programs, and re-execute updated programs and dependent programs for up- dated data/programs. In the system, a data analyzer can specify the dependency, parts for requiring distributed parallel processing using Hadoop Streaming, and they can be processed only for updated and dependent part, with flexibly selecting parallel or sequential execution. The specification can also specify multiple execution for the same program for different data as a simple statement, while their dependencies are checked separately.

その他リンク： http://www.f.ait.kyushu-u.ac.jp/kjjwonict/

仮想化の仮想 (Virtual Virtualization)

井上創造

情報処理学会誌：特集「日本を元気にするICT」 ( 情報処理学会誌：特集「日本を元気にするICT」 ) 53 ( 4 ) 394 - 397 2012年03月

予防医療に貢献する生体情報・健康情報モニタリングシステムの確立

井上創造, 中島直樹

月刊「自動認識」日本工業出版（株） ( 月刊「自動認識」日本工業出版（株） ) 2012年03月

記述言語：日本語掲載種別：記事・総説・解説・論説等（商業誌、新聞、ウェブメディア）

世界最速で少子高齢化社会が到来した日本において，労働生産性を確保し国力を維持するためには，精緻な健康医療情報を活用することが喫緊の課題となっている．本稿では，人々の日常の行動を把握し，生活の場における情報支援を安全に効率良く行うための，センサ技術を用いた予防医療システムに関する動向および研究成果を述べ，今後の研究の方向性を展望する．

Applying Unsupervised Segmentation to High-level Activity Recognition from Accelerometers on Mobile Phones 査読有り

井上創造, 服部祐一, 野原康伸, 中島直樹

Submitted to Springer 2 - 0 2012年02月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, we propose an application of unsupervised method for multi-level segmentation, which could be used for a pre-process of non-sequential activity recognition, and could construct a high-level activity recognition using ac- celerometers on mobile phones. We extend single-level segmentation to multi-level by sweeping the temporal parameter. We also describe the experience of activity data collecting system ALKAN, and collected large-scale nursing data for anno- tated rehearsal activities and real nursing activities for 41 activity classes. Using the segmentation method and the activity data, we demonstrate several application of the method to automatically segment real nursing data, to help annotation with a suggestion from the history, and to improve activity recognition accuracy.

Implementation of Activity Recognition From Accelerometers on Mobile Phones 査読有り

平川剛, Thin Thin Nwe, 服部祐一, 井上創造

3rd International Conference on Intelligent Networking and Collaborative Systems (INCoS 2011) 2 pages 2011年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Fukuoka Fukuoka

In this paper, we propose an experimental implementation of activity recognition feature on the activity information gathering system named ALKAN. In this experiment, we develop activity recognition algorithm using machine learning on server system, and port it onto client system on mobile phone. We also confirmed the feasibility of real-time activity recognition with actual mobile phone.

DOI： 10.1109/INCoS.2011.103

Scopus

その他リンク： http://voyager.ce.fit.ac.jp/~incos2011/

Visualization for Activity Information Sharing System Using Self-Organizing Map 査読有り

服部祐一, 井上創造, 平川剛

International Workshop on Network Traffic Control, Analysis and Applications (NTCAA-2011) 6 pages 2011年10月

Toward High-level Activity Recognition from Accelerometers on Mobile Phones

井上創造, 服部祐一

Proc. IEEE International Conference on Cyber, Physical and Social Computing (CPSCom 2011) 7 pages 2011年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Dalian, China Dalian, China

In this paper, we propose an unsupervised method for multi-level segmentation, which could be used for a pre- process of non-sequential activity recognition, and could con- struct a high-level activity recognition using accelerometers on mobile phones. We extend single-level segmentation to multi- level by sweeping the temporal parameter. To confirm the valid- ity of our approach. we pursued the experiment of gathering accelerometer data of real nursing in a hospital. After the experiment and multi-level segmentation, we confirmed several phenomena to imply the validity of multi-level segmentation such that sequence seems to be properly segmented fitting to the annotations transcribed from the voice, that there are peaks of lower-level segment boundaries without higher-level boundaries, and that higher-level boundaries are not lower- level boundaries.

DOI： 10.1109/iThings/CPSCom.2011.98

Scopus

その他リンク： http://cpscom.org/

Benchmarking ‘Radio Exercises’ Recognition with a Three-axis Accelerometer 査読有り

照本旭生, 井上創造, 服部祐一

SMC Workshop on Robust machine learning techniques for human activity recognition 5 pages 2011年10月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Anchorage, Alaska Anchorage, Alaska

In this paper, we introduce a method for recognizing actions in the 1st part of Radio Exercises, with a single smart phone equipped with three-axis accelerometers, which is placed in the breast pocket. Radio Exercises is a warm-up calisthenics performed with music and chants. We obtained the acceleration data of smart phones placed at the breast pockets to a fixed direction of 4 members. For gathered 44 action data, we extracted time windows, and calculated the Fourier transformation for each axis, and adopted the values of from 0.25Hz to 5Hz as a feature vector. Upon the feature vector, we applied principal component extraction, and applied several machine learning algorithms to from 1st to 8th principal components. The benchmarked value resulted in 64.10% of accuracy in the best method, and we could find out what action is easier or difficult to recognize.

Kyutacar

その他リンク： http://www.opportunity-project.eu/workshopSMC

Challenges for Activity Recognition with Real Data 査読有り

井上創造

Ubicomp Workshop on Mobile Sensing: Challenges, Opportunities and Future Directions 2011 2 pages 2011年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Beijing, China Beijing, China

In this paper, we introduce a large-scale activity data col- lection, and discuss the challenges for activity recognition with real data. We address the requirements of annotation for sequential activities and of utilizing device status, and also address research directions for unsupervised methods and complementary information.

その他リンク： http://research.microsoft.com/en-us/um/beijing/events/ms_ubicomp11/

HASC2011corpus: Towards the Common Ground of Human Activity Recognition 査読有り

河口信夫, Ying Yang, Tianhui Yang, 小川延宏, 岩崎陽平, 梶克彦, 寺田努, 村尾和哉, 井上創造, 川原圭博, 角康之, 西尾信彦

Proc. International Conference on Ubiquitous Computing (Ubicomp 2011) Poster 571 - 572 2011年09月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）

Beijing, China Beijing, China

Human activity recognition through the wearable sensor will enable a next-generation human-oriented ubiquitous computing. However, most of research on human activity recognition so far is based on small number of subjects, and non-public data. To overcome the situation, we have gathered 4897 accelerometer data with 116 subjects and compose them as HASC2011corpus. In the field of pattern recognition, it is very important to evaluate and to improve the recognition methods by using the same dataset as a common ground. We make the HASC2011corpus into public for the research community to use it as a common ground of the Human Activity Recognition. We also show several facts and results of obtained from the corpus.

DOI： 10.1145/2030112.2030218

Scopus

その他リンク： http://dl.acm.org/citation.cfm?doid=2030112.2030218

A Large Scale Gathering System for Activity Data using Mobile Devices 査読有り

服部祐一, 井上創造

Journal of Information Processing 20 ( 1 ) 177 - 184 2011年09月

記述言語：英語掲載種別：研究論文（学術雑誌）

In this paper, we introduce a large-scale activity gathering system with mo- bile sensor devices such as smart phones and accelerometers. We gathered over 35,000 activity data from more than 200 people approximately 13 months. We describe the design rationale of the system, analyze the gathered data through statistics and clustering, and application of an existing activity recognition method. From the recognition, the performance of existing algorithm drasti- cally deteriorated using the gathered data as training data. This results show that we found still a challenging field for activity recognition in larger-scale activity data.

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ここに掲載した著作物の利用に関する注意本著作物の著作権は情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。

情報爆発時代のヘルスケア(Healthcare in the Info-plosion Era)

井上創造, 中島直樹

電子情報通信学会誌 ( 電子情報通信学会誌 ) 94 ( 8 ) 700 - 705 2011年08月

記述言語：日本語掲載種別：記事・総説・解説・論説等（その他）

生活習慣病予防医療のために生体センサネットワークを実際に100人の被験者に2週間，50人の患者に3ヶ月間つけてもらい，生活習慣の自動記録による労力削減と，データ解析基盤を同時に実現し，日常においてリスクの高い患者の発見や，データに基づくフィードバックの効果を実証した．

A Large Scale Gathering System for Activity Data with Mobile Sensors 査読有り

服部祐一, 井上創造, 平川剛

IEEE International Symposium on Wearable Computers (ISWC2011) 97 - 100 2011年06月

Location Recognition in RFID Bookshelves 査読有り

井上創造, 野原康伸, 竹森正起, 櫻川幸三

IEICE Transaction, Vol. E94-D ( 6 ) 1147 - 1152 2011年06月

記述言語：英語掲載種別：研究論文（学術雑誌）

RFID書架における位置の読み取り誤りに対して，単純ベイズ分類器を用いて改善する手法を提案し，12658回の試行について78.6%の精度を得た．またこの学習の一般性について確認するため，ブロック毎に学習したり，本毎に学習する方法を比較し、ブロックや本が変わったときにどの程度精度に影響が出るかを確認した．

DOI： 10.1587/transinf.E94.D.1147

Scopus

CiNii Article

HASC Challenge: Gathering Large Scale Human Activity Corpus for the Real-World Activity Understandings 査読有り

河口信夫, 小川延宏, 岩崎陽平, 梶克彦, 寺田努, 村尾和哉, 井上創造, 川原圭博, 角康之, 西尾信彦

Proc. Augmented Human Conference ( 27 ) 1 - 5 2011年03月

Community Based Feature Database Construction for Mobile Image Retrieval

高野茂, 馬場謙介, 井上創造

Proc. IADIS e-Society 2011 (ES 2011) Conference (Poster/Demo) 580 - 582 2011年03月

Activity Information Sharing System with Video and Acceleration Data 査読有り

平川剛, 服部祐一, 中村優斗, 井上創造

Proc. Int'l Conf. Pervasive and Embedded Computing and Communication Systems 557 - 561 2011年03月

Gathering Large Scale Human Activity Information Using Mobile Sensor Devices 査読有り

服部祐一, 井上創造, 平川剛, 須藤修

Proc. International Workshop on Network Traffic Control, Analysis and Applications (NTCAA-2010) 708 - 713 2010年11月

A Secure and Scalable Identification for Hash-based RFID Systems Using Updatable Pre-computation 査読有り

野原康伸, 井上創造

Proc. 3rd ACM Conf. Wireless Network Security(Wisec'10) 65 - 74 2010年03月

On the Observability of RFID Data Privacy 査読有り

井上創造, 野原康伸

Proc. Int'l WS Network Traffic Control, Access, and Applications(NTCAA) 714 - 718 2009年12月

An Efficient Identification and Indexing for Secure RFID with d-Left Hashing 査読有り

野原康伸, 井上創造

DBSJ Journal 8 ( 2 ) 7 - 12 2009年09月

Toward Accurate Location Detection in RFID Bookshelves 査読有り

野原康伸, 井上創造, 竹森正起, 櫻川幸三

Proc. Int'l Symp. Ubiquitous Computing Systems(UCS) 2009 99 - 104 2009年08月

韓国にみる図書館の新しい動き

吉松直美, 兵藤健志, 牧瀬ゆかり, 南俊朗, 井上創造, 金銀子

九州大学附属図書館研究開発室年報 2008 46 - 55 2009年07月

機関リポジトリ担当者の人材育成について : CSI委託事業「持続可能な機関リポジトリのための人材進化構造」講習会報告

星子奈美, 井上創造

九州大学附属図書館研究開発室年報 2008 34 - 39 2009年07月

記述言語：日本語掲載種別：研究論文（大学，研究機関等紀要）

平成20年度，九州大学附属図書館において，機関リポジトリを永続的に運用するために必要な人材育成を目的とした講習会が開催された．これは，国立情報学研究所の委託事業によるもので，事業連携大学をはじめとして，北は北海道，南は沖縄からの参加者もあり，学内外から毎回約20名の受講者が参加した．受講者は，html言語やPHP言語等を題材にシステムに関する概念やwebシステム開発の基礎知識と技術を学んだ．全3回，各回2日間(約10時間)，講義を受け，演習・発表を行い，次回に向けての宿題も課せられた．また，個人のスキルアップのみでなく，講習会後は受講者が主軸となり，講習会の内容を波及させていったことが今回の講習会の特徴である．

Kyutacar

その他リンク： http://ci.nii.ac.jp/naid/120001469071

Access Flows to a Repository from Other Services 査読有り

池田大輔, 井上創造

Open Repositories 2009 (Poster) 4 pages 2009年05月

Construction and Use Examples of Private Electronic Notary Service in Educational Institutions 査読有り

Masanori Nakakuni, Eisuke Ito, Yoshiaki Kasahara, 井上創造, Hiroshi Dozono

WSEAS Transaction on Advances in Engineering Education, Issue 1, ISSN: 1790-1979 5 676 - 686 2008年11月

研究活動支援のためのSNSとWebサービスの連携 : flickrにおけるプロトタイプ実装

池田大輔, 木藤基樹, 馬場慎也, 井上創造

九州大学附属図書館研究開発室年報 2007 12 - 16 2008年10月

図書館におけるWebアプリケーション開発と人材育成について

兵藤健志, 井上創造, 牧瀬ゆかり

九州大学附属図書館研究開発室年報 2007 1 - 7 2008年10月

種々の画面サイズに対応した仮想書架Webインタフェース

井上創造, 小山健一郎

九州大学附属図書館研究開発室年報 2007 8 - 11 2008年10月

学術情報リポジトリ活性化のための足跡機能

井上創造, 藤井達朗, 小材健, 池田大輔

九州大学附属図書館研究開発室年報 2007 17 - 22 2008年10月

eService Innovation and Sensor Based Healthcare

須藤修, 井上創造, 中島直樹

Proc. IFIP International Federation for Information Processing, Springer Boston 286 1 - 14 2008年08月

A Sustainable Model based on the Social Network Service to Support the Research Cycle 査読有り

池田大輔, 井上創造

Proc. of The 3rd International Conference on Open Repositories 4 pages 2008年04月

A Secure High-Speed Identification Scheme for RFID Using Bloom Filters 査読有り

野原康伸, 井上創造, 安浦寛人

Proc. of 3rd International Conference on Availability, Reliability and Security (ARES) 717 - 722 2008年03月

Protecting Global Medical Telemetry Infrastructure 査読有り

Benessa Defend, Mastooreh Salajegheh, Kevin Fu, 井上創造

I3P White Paper 1 - 5 2008年01月

A New, Sustainable Model for the Institutional Repository: A CSI Project 'integration and Presentation of Diverse Information Resources' 査読有り

井上創造, 池田大輔

DRF Int’l Conf. 2008 5 - 8 2008年01月

Trustworthy SNS for Institutional Repositories 査読有り

井上創造, 堀優子, 池田大輔

DRF International Conference 1 page 2008年01月

IR and RI: Smooth Use from External Systems 査読有り

小野真由美, 井上創造, 星子奈美

DRF International Conference 1 page 2008年01月

Toward Efficient Identification for Privacy-preserving Hash-based RFID Schemes 査読有り

野原康伸, 井上創造, 安浦寛人

International Workshop on Real Field Identification 0 46 - 51 2007年11月

RFID Application for Library 査読有り

井上創造, Daisuke Miyaoka, 池田大輔, 南俊朗, Kiyotaka Fujisaki

International Workshop on Real Field Identification 0 31 - 38 2007年11月

UMASS Amherst校図書館視察報告

井上創造

九州大学附属図書館研究開発室年報 2006 43 - 49 2007年10月

研究者業績情報システムと学術情報リポジトリの連携

小野真由美, 井上創造, 星子奈美, 森雅生

九州大学附属図書館研究開発室年報 2006 1 - 9 2007年10月

非接触ICカードの原理と体系化

井上創造, 安浦寛人

九州大学附属図書館研究開発室年報 2006 20 - 25 2007年10月

SNSにおける新しい信頼モデルと図書館における応用

井上創造, 堀優子

九州大学附属図書館研究開発室年報 2006 22 - 29 2007年10月

電子ペーパーが創るユビキタス社会 —電子ペーパークライアントを目指して—

服部励治, 井上創造

情報処理学会誌 ( 情報処理学会誌 ) 28 ( 8 ) 873 - 883 2007年08月

非接触ICカード技術の概観と展望

井上創造, 安浦寛人

情報処理学会誌 ( 情報処理学会誌 ) 48 ( 6 ) 551 - 555 2007年06月

Unlinkability and Real World Constraints in RFID Systems 査読有り

野原康伸, 井上創造, 安浦寛人

Proc. Pervasive RFID/NFC Technology and Applications Workshop 371 - 376 2007年03月

RFIDを利用した救急トリアージシステムの実証実験査読有り

園田章人, 井上創造, 岡賢一郎, 藤崎伸一郎

情報処理学会論文誌 48 ( 2 ) 802 - 810 2007年02月

記述言語：日本語掲載種別：研究論文（学術雑誌）

RFIDを利用した救急トリアージのシステムとその実証実験について述べる．本研究では，RFIDとモバイルネットワークを利用して，負傷者の情報収集および搬送を効率的に行うシステムを提案し，80名程度の負傷者を想定した実証実験を行った結果，負傷者の搬送時間の短縮と，確実かつ迅速な情報収集ができた.

Kyutacar

Triage with RFID Tags 査読有り

井上創造, 園田章人, 岡賢一郎, 藤崎伸一郎

Proc. 1st International Conference on Pervasive Computing Technologies for Healthcare 7 pages 2006年11月

Unlinkable Identification for Large-scale RFID Systems 査読有り

野原康伸, 中村徹, 馬場謙介, 井上創造, 安浦寛人

IPSJ Journal 47 ( 8 ) 2362 - 2370 2006年08月

記述言語：英語掲載種別：研究論文（学術雑誌）

同じ所持者のデバイスからの出力かどうかを攻撃者が判定できないというリンク不能性を満たす識別は，既存の方法ではRFIDタグの数Nに対しO(N)回のハッシュ計算が必要だったが，本稿ではO(log N)回に削減する方法を提案し理論的に評価した上で，実際のシステムに実装し結果した．

RFIDを用いた学会参加者ネットワーク表示システムとその利用

井上創造, 木實新一, 小林隆志, 土田正士, 喜連川優

日本データベース学会Letters 5 ( 1 ) 81 - 84 2006年06月

Systematic Error Detection for RFID Reliability 査読有り

井上創造, 萩原大輔, 安浦寛人

International Conference on Availability, Reliability and Security (ARES) 280 - 286 2006年04月

On Authentication between Human and Computer 査読有り

渡部貴大, 野原康伸, 馬場謙介, 井上創造

IEEE International Conference on Pervasive Computing and Communications (PerCom) Workshops 636 - 639 2006年03月

Emergency Healthcare Support: RFID Based Massive Injured People Management 査読有り

井上創造, 園田章人, 岡賢一郎, 藤崎伸一郎

Proc. Pervasive Healthcare Workshop in Ubicomp 2006 (UbiHealth) 9 pages 2006年01月

自動認識におけるプライバシーと個人情報保護技術

井上創造, 野原康伸, 安浦寛人

電子情報通信学会誌 ( 電子情報通信学会誌 ) 89 ( 5 ) 390 - 394 2006年01月

記述言語：日本語掲載種別：記事・総説・解説・論説等（その他）

本稿では,RFIDを用いたシステムのプライバシと個人情報保護に関する問題を明確にした．本稿ではプライバシーと個人情報保護を区別した上で，匿名性とリンク不能性という性質の異なる概念を導入した．また既存の技術をこれらの観点及び，システムやRFIDタグのコストの観点から分類した．

RFID情報システムにおけるシステムレベルでの信頼性向上査読有り

萩原大輔, 井上創造, 安浦寛人

情報処理学会論文誌:データベース(TOD26) 46 ( 0 ) 37 - 47 2005年01月

An RFID-based Multi-service System for Supporting Conference Events 査読有り

渡部貴大, 井上創造, 安浦寛人, Jun Sasaki, Yasushi Aoki, Kazumi Akimoto

International Conference on Active Media Technology (AMT) 435 - 439 2005年01月

Quantitative Evaluation of Unlinkable ID Matching Schemes 査読有り

野原康伸, 井上創造, 馬場謙介, 安浦寛人

ACM Conference on Computers and Communications Security (CCS) Workshop in the Electronic Society 55 - 60 2005年01月

Toward Unlinkable ID Management for Multi-service Environments 査読有り

野原康伸, 井上創造, 安浦寛人

IEEE International Conference on Pervasive Computing and Communications (PerCom) Workshops 115 - 119 2005年01月

RFID情報システムにおけるシステム信頼性の向上

井上創造, 萩原大輔, 安浦寛人

日本データベース学会Letters 3 ( 4 ) 13 - 16 2005年01月

A Systematic Approach for the Reliability of RFID Systems 査読有り

井上創造, 萩原大輔, 安浦寛人

IEEE TENCON 183 - 186 2004年01月

Aspects of Privacy for RFID Systems

井上創造

International Workshop Series on RFID web publication 2004年01月

RFID Privacy Using User-Controllable Uniqueness 査読有り

井上創造, 安浦寛人

RFID Privacy Workshop Web Publication 2003年01月

コミュニケーションを用いた作業プロセスの動的な獲得査読有り

井上創造, 岩井原瑞穂

情報処理学会論文誌:データベース 42 ( 0 ) 50 - 62 2002年01月

記述言語：日本語掲載種別：研究論文（学術雑誌）

本論文では，構造があらかじめ明確には定義されず, 実行と並行して人間同士の議論によって詳細化されるコミュニケーションプロセスを提案し, 有効性を評価した．これはプロセスとコミュニケーションを統合するモデルであり，局所的に変更を許す方法と, 過去の記録に基づいて変更する方法を提供した．

Development and Operation of a Document Database for University Research and Education Activities 査読有り

野中裕介, 井上創造, 秦野克彦, 原田努, 乃村能成, 岩井原瑞穂, 峯恒憲, 牛島和夫

Systems and Computers in Japan 33 ( 0 ) 41 - 53 2002年01月

記述言語：英語掲載種別：研究論文（学術雑誌）

Webを通じた各教官による研究教育活動報告書の入力や，管理者による公開を行うためのシステムを開発し評価した．リレーショナルとSGMLを混在させることで各教官毎にフォーマットを選択できるようにした．また分散管理による運用負担軽減や, 修正時の修正箇所を限定できていることを評価した．

Kyutacar

Supporting Dynamic Process Specifications using Communication based Processes 査読有り

井上創造, 岩井原瑞穂

Hawaii International Conference on System Sciences CD-ROM 2002年01月

Privacy in the Digitally Named World with RFID Tags 査読有り

井上創造, 木實新一, 安浦寛人

Workshop on Socially-informed Design of Privacy-enhancing Solutions in UbiComp 2002 Web Publication 2002年01月

RFIDタグを用いた安全で効率の良いデジタルネーミング社会について

井上創造, 安浦寛人

九州大学大学院システム情報科学紀要 7 ( 2 ) 131 - 137 2002年01月

教官の研究教育活動等報告書データベースシステムの開発と運用査読有り

野中裕介, 井上創造, 秦野克彦, 原田努, 乃村能成, 岩井原瑞穂, 峯恒憲, 牛島和夫

電子情報通信学会論文誌 0 ( 1 ) 974 - 986 2001年01月

非同期型コミュニケーションにおけるトランザクションの動的構築査読有り

井上創造, 岩井原瑞穂

情報処理学会論文誌:データベース 40 ( 0 ) 1 - 12 1999年01月

記述言語：日本語掲載種別：研究論文（学術雑誌）

電子メールに代表される蓄積型のメッセージのやりとりに対しトランザクション管理を行なう手法を提案した．本手法により，利用者やシステムが作業の状態を把握できるようになり，データベースとの連動も可能になる．またプロトタイプシステムについて述べ，本モデルの実用性を評価した結果を示す．

Adapting Transactions to Exceptional Situations Using Structured Messages 査読有り

井上創造, 岩井原瑞穂

International Symposium on Database Applications in Non-Traditional Environments (DANTE), IEEE Press 351 - 358 1999年01月

Structured Message Management for Group Interaction 査読有り

井上創造, 岩井原瑞穂

International Workshop on New Database Technologies for CSCW and Spatio-Temporal Data Management (NewDB) 0 398 - 407 1998年01月

On Unifying Message and Transaction Management for Collaborative Design Work 査読有り

岩井原瑞穂, 井上創造, Hiroki Matsuo

International Symposium on Digital Media Information Base (DMIB) 300 - 304 1997年01月

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection 査読有り国際誌

Ronando, Elsen; Inoue, Sozo;

Sensors ( MDPI ) 25 ( 11 ) 3324 - 3324 2025年05月

Nurse Activity Recognition in Gastrostomy Tube Feeding Using Video-Based Pose with Large Language Model-Guided Features 査読有り国際誌

Zhao, Lingfeng; Garcia, Christina; Komizunai, Shunsuke; Colley, Noriyo; Sato, Atsuko; Kouchiyama, Mayumi; Nasu, Toshiko; Inoue, Sozo;

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 28 2025年05月

Domain Knowledge Integration with Chain of Thought and Knowledge Prompting in Text to Motion Generation 査読有り国際誌

Hassan, Iqbal; Nahid, Nazmun; Inoue, Sozo;

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 25 2025年05月

Extraction and Summarization from Visiting Nurse Transcriptions Using Improved Prompt Techniques 査読有り国際誌

Shoumi, Milyun Ni’ma; Hamdhana, Defry; Harada, Kazumasa; Oshita, Hitomi; Sakashita, Satomi; Inoue, Sozo;

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 50 2025年05月

Summary of the Virtual Data Generation for Complex Industrial Activity Recognition 査読有り国際誌

Xia, Qingxin; Garcia, Christina; Dobhal, Umang; Xinyi, Min; Kei, Tanigaki; Inoue, Sozo; Maekawa, Takuya; Wu, Kaishun;

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 2 ) 1 - 12 2025年05月

Toward Abnormal Activity Recognition of Developmentally Disabled Individuals Using Pose Estimation 査読有り国際誌

Fujioka, Taihei; Garcia, Christina; Inoue, Sozo;

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 28 2025年05月

Advancing Heatstroke Prevention: Integrating Physiological Data for Enhanced Thermal Comfort Forecasting 査読有り国際誌

Hossain, Tahera; Tazin, Tahia; Garcia, Christina; Honda, Kazuki; Inoue, Sozo; Lopez, Guillaume;

Activity, Behavior, and Healthcare Computing ( CRC Press ) 257 - 274 2025年02月

Toward Detecting and Explaining Stress of Nurses Using Wearable Devices and LLMs 査読有り国際誌

Miyake, Naoya; Kaneko, Haru; Ronando, Elsen; Garcia, Christina; Inoue, Sozo;

International Conference on Ubiquitous Computing and Ambient Intelligence ( Springer Nature Switzerland Cham ) 288 - 299 2024年11月

Preliminary Investigation of Activity Prediction in Nursing Homes using Activity History with Erroneous Time Stamps 査読有り国際誌

Okuda, Ryuichiro; Qingxin, Xia; Takuya, Maekawa; Hara, Takahiro; Inoue, Sozo;

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 851 - 855 2024年10月

Synthetic Skeleton Data Generation using Large Language Model for Nurse Activity Recognition 査読有り国際誌

Dobhal, Umang; Garcia, Christina; Inoue, Sozo;

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 493 - 499 2024年10月

A Monocular Fisheye Video-Based 2D to 3D Pose Lift Technique with Multiperson Spatial Context Integration 査読有り国際誌

Hassan, Iqbal; Nahid, Nazmun; Inoue, Sozo;

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 475 - 480 2024年10月

Large Language Models for Generating Semantic Nursing Activity Logs: Exploiting Temporal and Contextual Information 査読有り国際誌

Nahid, Nazmun; Munemoto, Ryuya; Inoue, Sozo;

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 481 - 486 2024年10月

Elderly Motion Analysis to Estimate Emotion: A Systematic Review 査読有り国際誌

Iqbal Hassan, Nazmun Nahid, Md Atiqur Rahman Ahad, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 23 2024年06月

Nurses' Skill Assessment in Endotracheal Suctioning Using Video-based Activity Recognition 査読有り国際誌

Hoang Anh Vy Ngo, Noriyo Colley, Shinji Ninomiya, Satoshi Kanai, Shunsuke Komizunai, Atsushi Konno, Misuzu Nakamura, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 24 2024年06月

Integrating Human Behavioral Model for Safe Intimate-distance Human Robot Collaboration 査読有り国際誌

Nazmun Nahid, Iqbal Hassan, Xinyi Min, Naoya Ryoke, Md Atiqur Rahman Ahad, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 26 2024年06月

Leveraging the Large Language Model for Activity Recognition: A Comprehensive Review 査読有り国際誌

Milyun Ni’ma Shoumi, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 27 2024年06月

Toward Extracting Care Records from Transcriptions of Visiting Nurses Using Large Language Models 査読有り国際誌

Defry Hamdhana, Kazumasa Harada, Hitomi Oshita, Satomi Sakashita, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 17 2024年06月

Improving Fatigue Detection with Feature Engineering on Physical Activity Accelerometer Data Using Large Language Models 査読有り国際誌

Elsen Ronando, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 22 2024年06月

Toward Recognizing Nursing Activity in Endotracheal Suctioning Using Video-based Pose Estimation 査読有り国際誌

Hoang Anh Vy Ngo, Quynh N Phuong Vu, Noriyo Colley, Shinji Ninomiya, Satoshi Kanai, Shunsuke Komizunai, Atsushi Konno, Misuzu Nakamura, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 20 2024年05月

Synchronizing an AR Robot Simulator with a Real Industrial Robot 査読有り国際誌

Naoya Ryoke, Nazmun Nahid, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 20 2024年05月

Forecasting Sit-to-Stand Transitions in Wheelchair Patients: a Textile Pressure Sensor-based Approach 査読有り国際誌

Tahia Tazin, John Noel Victorino, Sozo Inoue, Yu Enokibori

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 20 2024年05月

Evaluation of Functional Estimation Methods in IoT Devices at Intervals of a Few Seconds by Communication Traffic Analysis 査読有り国際誌

Yuichi Hattori, Yutaka Arakawa, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 19 2024年05月

A Relabeling Approach to Signal Patterns for Beacon-based Indoor Localization in Nursing Care Facility 査読有り国際誌

Chrisitina A. Garcia, Quynh N Phuong Vu, Haru Kaneko, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 19 2024年05月

Improved Evaluation Metrics for Sentence Suggestions in Nursing and Elderly Care Record Applications 査読有り国際誌

Defry Hamdhana, Haru Kaneko, John Noel Victorino, Sozo Inoue

Healthcare ( MDPI ) 12 ( 3 ) 367 2024年01月

Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities 査読有り国際誌

Christina Garcia, Sozo Inoue

Sensors ( MDPI ) 24 ( 2 ) 319 2024年01月

Estimate of Cat Excretion Information Using Multiple Weight Sensors 査読有り国際誌

Tetsuhiro Yamaguchi, Namiko Nakashima, Takeshi Shigemori, Teruki Hirahata, Sozo Inoue

International Conference on Informatics, Electronics & Vision (ICIEV) & International Conference on Imaging, Vision & Pattern Recognition (icIVPR) ( CRC press ) 2023年10月

Toward Pioneering Sensors and Features Using Large Language Models in Human Activity Recognition 査読有り国際誌

Haru Kaneko, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) ( ACM ) 2023年10月

Predicting and Analyzing Emotion of Elderly People in Care Facilities 査読有り国際誌

Xinyi Min, Haru Kaneko, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) ( ACM ) 457 - 462 2023年10月

Function-level Access Control System for Home IoT Devices 査読有り国際誌

服部祐一, 荒川豊, Daichi Koike, Shigemi Ishida, 井上創造

Sensors and Materials 34 ( 6 ) 2125 - 2139 2022年06月

Toward the Analysis of Office Workers’ Mental Indicators Based on Wearable, Work Activity, and Weather Data 査読有り国際誌

西村勇亮, Tahera Hossain, Akane Sano, 磯村昇太, 荒川豊, 井上創造

International Conference on Activity and Behavior Computing (ABC) 1 - 26 2021年10月

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