Faculty Profiles - INOUE Sozo

Papers - INOUE Sozo

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Optimizing Forecasted Activity Notifications with Reinforcement Learning Reviewed International journal

Muhammad Fikry, Sozo Inoue

Sensors ( MDPI ) 23 ( 14 ) 6510 2023.07

A Bayesian Approach for Quantifying Data Scarcity when Modeling Human Behavior via Inverse Reinforcement Learning Reviewed International journal

Tahera Hossain, Wanggang Shen, Anindya Antar, Snehal Prabhudesai, Sozo Inoue, Xun Huan, Nikola Banovic

ACM Transactions on Computer-Human Interaction ( ACM ) 30 ( 1-8 ) 1 - 27 2023.03

Improving Noise Robustness of Single Sensor Data in Human Activity Recognition With UMAP and Additional Data Reviewed International journal

Quynh Nguyen Phuong VU, Paula Lago, Sozo Inoue

ISWC '22: Proceedings of the 2022 ACM International Symposium on Wearable Computers ( ACM ) 109 - 111 2022.12

Handling Class Imbalance in Forecasting Parkinson's Disease Wearing-off with Fitness Tracker Dataset Reviewed International journal

John Noel Victorino, Sozo Inoue, Tomohiro Shibata

International Conference on Neural Information Processing (ICONIP2023) 564 - 578 2023.11

Psychological Analysis in Human-Robot Collaboration from Workplace Stress Factors: A Review Reviewed International journal

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

Activity and Behavior Computing (to appear) ( CRC press ) 2023.06

Summary of the Fourth Nurse Care Activity Recognition Challenge - Predicting Future Activities Reviewed International journal

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

Activity and Behavior Computing (to appear) ( CRC press ) 2023.06

Improving Complex Nurse Care Activity Recognition Using Barometric Pressure Sensors Reviewed International journal

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 ) 2023.06

Challenges and Opportunities of Activity Recognition in Clinical Pathways Reviewed International journal

Chrisitina A Garcia, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023.06

Analysis of Care Records for Predicting Urination Times Reviewed International journal

Masato Uchimura, Haru Kaneko, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023.06

Forecasting Parkinson's Disease Patients' Wearing-Off using Wrist-Worn Fitness Tracker and Smartphone Dataset Reviewed International journal

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

Activity and Behavior Computing (to appear) ( CRC press ) 2023.06

Understanding Mental Health Using Ubiquitous Sensors and Machine Learning: Challenges Ahead Reviewed International journal

Tahia Tazin, Tahera Hossain, Shahera Hossain, Sozo Inoue

Activity and Behavior Computing (to appear) ( CRC press ) 2023.06

Summary of the Third Nurse Care Activity Recognition Challenge - Can We Do from the Field Data? Reviewed International journal

Sayeda Shamma Alia, Kohei Adachi, Tahera Hossain, Le Nhat Tan, Haru Kaneko, Paula Lago, Tsuyoshi Okita, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021.09

Transition-points-based Segmentation and Hierarchical Classification for Locomotion and Transportation recognitionon Radio-data Reviewed International journal

Le Nhat Tan, Nazmun Nahid, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021.09

Analysis of Feature Importances for Automatic Generation of Care Records Reviewed International journal

Haru Kaneko, Tahera Hossain, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021.09

PerMML: A Performance Metric for Multi-layer Dataset Reviewed International journal

Sayeda Shamma Alia, Tahera Hossain, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 2021.09

Integrating A Spoken Dialogue System, Nursing Records, and Activity Data Collection based on Smartphones Reviewed International journal

Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue

Computer Methods and Programs in Biomedicine, ISSN 0169-2607 106364 2021.08

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://doi.org/10.1016/j.cmpb.2021.106364.

Intracranial Hemorrhage Brain Image Non-rigid Registration from Real-world Dataset to Reference Space Reviewed International journal

Le Nhat Tan, Shoji Kobashi, Koichi Arimura, Koji Iihara, Sozo Inoue

International Conference on Imaging, Vision & Pattern Recognition (IVPR) 7 pages 2021.08

Language：English Publishing type：Research paper (international conference proceedings)

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 Reviewed International journal

John Noel Victorino, Yuko Shibata, Sozo Inoue, Tom Shibata

Applied Sciences, MDPI 11 ( 16 ) 2 - 2 2021.08

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://www.mdpi.com/2076-3417/11/16/7354

CrowdAct: Achieving High-Quality Crowdsourced Datasets in Mobile Activity Recognition Reviewed International journal

Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue

Proc. of ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Article 142, 5 ( 0 ) 3 - 2 2021.03

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： 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]

Sozo Inoue

36 ( 2 ) 233 - 246 2021.03

Estimation of Record Contents for Automatic Generation of Care Records Reviewed International journal

Haru Kaneko, Tahera Hossain, Sozo Inoue

Activity and Behavior Computing, Springer Nature 289 - 306 2021.01

Language：English Publishing type：Research paper (scientific journal)

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.

Other Link： https://link.springer.com/chapter/10.1007/978-981-15-8944-7_18

Exploring Human Activities Using eSense Earable Device Reviewed International journal

Md. Shafiqul Islam, Tahera Hossain, Md Atiqur Rahman Ahad, Sozo Inoue

Activity and Behavior Computing, Springer Nature 169 - 185 2021.01

Improvement of Human Action Recognition Using 3D Pose Estimation Reviewed International journal

Kohei Adachi, Paula Lago, Tsuyoshi Okita, Sozo Inoue

Activity and Behavior Computing, Springer Nature 21 - 37 2021.01

Summary of the Cooking Activity Recognition Challenge Reviewed International journal

Sayeda Shamma Alia, Paula Lago, Shingo Takeda, Kohei Adachi, Brahim Brenaissa, Md Atiqur Rahman Ahad, Sozo Inoue

Human Activity Recognition Challenge, Springer Nature 1 - 13 2021.01

Multilabel Classification of Nursing Activities in a Realistic Scenario Reviewed International journal

Farina Faiz, Yoshinori Ideno, Sozo Inoue

Activity and Behavior Computing, Springer Nature 269 - 288 2021.01

On-Device Deep Personalization for Robust Activity Data Collection Reviewed International journal

Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue

Sensors, MDPI 21 ( 41 ) 2 - 2 2020.12

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://doi.org/10.3390/s21010041

Implementation of Care Records Automatic Generation Function in a Care Record Application Reviewed International journal

Haru Kaneko, Tahera Hossain, Sozo Inoue

The 40th Joint Conference on Asia-Pacific Association of Medical Informatics (APAMI) 6 pages 2020.12

Language：English Publishing type：Research paper (international conference proceedings)

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 Reviewed International journal

Muhammad Fikry, Defry Hamdhana, Paula Lago, Sozo Inoue

Contactless Human Activity Analysis, Springer Nature 0 2 - 2 2020.12

Language：English Publishing type：Research paper (scientific journal)

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 Reviewed International journal

Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue

The 40th Joint Conference on Asia-Pacific Association of Medical Informatics (APAMI) 8 pages 2020.11

Language：English Publishing type：Research paper (international conference proceedings)

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 Reviewed International journal

Defry Hamdhana

Proceedings of the Conference on Embedded Networked Sensor Systems (SenSys) 807 - 808 2020.11

Language：English Publishing type：Research paper (international conference proceedings)

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 ...

Other Link： https://doi.org/10.1145/3384419.3430577

Multilabel classification in human activity recognition: PhD forum abstract Reviewed International journal

Farina Faiz

Proceedings of the Conference on Embedded Networked Sensor Systems (SenSys) 809 - 810 2020.11

Language：English Publishing type：Research paper (international conference proceedings)

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 ...

Other Link： https://doi.org/10.1145/3384419.3430578

Requirements analysis for reminder system in daily activity recognition dementia: PhD forum abstract Reviewed International journal

Muhammad Fikry

Proceedings of the Conference on Embedded Networked Sensor Systems (SenSys) 815 - 816 2020.11

Language：English Publishing type：Research paper (international conference proceedings)

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.

Other Link： https://doi.org/10.1145/3384419.3430572

Improving Activity Data Collection with On-device Personalization Using Fine-tuning Reviewed International journal

Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 255 - 260 2020.09

WorkerSense: Mobile Sensing Platform for Collecting Physiological, Mental, and Environmental State of Office Workers Reviewed International journal

Yuri Tani, Shuichi Fukuda, Yuki Matsuda, Sozo Inoue

PerHealth 2020: 5th IEEE PerCom Workshop on Pervasive Health Technologies (PerHealth 2020) 2020.09

Language：English Publishing type：Research paper (international conference proceedings)

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.

Improving Fine-tuned Question Answering Models for Electronic Health Records Reviewed International journal

Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue

Ubicomp Workshop on Computing for Well-Being (WellComp) 688 - 691 2020.09

Language：English Publishing type：Research paper (international conference proceedings)

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

Other Link： https://doi.org/10.1145/3410530.3414436

MCoMat: a New Performance Metric for Imbalanced Multi-layer Activity Recognition Dataset Reviewed International journal

Sayeda Shamma Alia, Paula Lago, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 232 - 237 2020.09

Language：English Publishing type：Research paper (international conference proceedings)

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

Other Link： https://doi.org/10.1145/3410530.3414364

Summary of the 2nd Nurse Care Activity Recognition Challenge Using Lab and Field Data Reviewed International journal

Sayeda Shamma Alia, Paula Lago, Kohei Adachi, Tahera Hossain, Hiroki Goto, Tsuyoshi Okita, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 378 - 383 2020.09

Language：English Publishing type：Research paper (international conference proceedings)

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

Other Link： https://doi.org/10.1145/3410530.3414611

Automatic Labeled Dialogue Generation for Nursing Record Systems Reviewed International journal

Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue

JPM Journal of Personalized Medicine 10 ( 3 ) 6 - 2 2020.09

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://doi.org/10.3390/jpm10030062

Towards Mapping Activity Classes for Transfer Learning in Human Activity Recognition Reviewed International journal

Md. Shafiqul Islam, Sayeda Shamma Alia, Sozo Inoue

International Conference on Activity and Behavior Computing (ABC) 5 pages 2020.08

Synthesizing Cell Protein data for Human Protein Cell Profiling Using Dual Deep Generative Modeling Reviewed International journal

Rakesh Ranjan, Sozo Inoue, Tom Shibata

International Conference on Imaging, Vision & Pattern Recognition (IVPR) 1 - 6 2020.08

Language：English Publishing type：Research paper (international conference proceedings)

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.

Other Link： https://ieeexplore.ieee.org/document/9306574

Exploring the Use of Accelerometer for Assisting Weight Lifting Exercise Reviewed International journal

Nour Al Bogha, Sozo Inoue, Brahim Brenaissa

International Conference on Activity and Behavior Computing (ABC) 1 - 4 2020.08

Language：English Publishing type：Research paper (international conference proceedings)

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.

Other Link： https://abc-research.github.io/2020/

Towards New Performance Metrics for Multi-level Data for Activity Recognition Reviewed International journal

Sayeda Shamma Alia, Paula Lago, Sozo Inoue

International Conference on Activity and Behavior Computing (ABC) 1 - 8 2020.08

A Method for Sensor-Based Activity Recognition in Missing Data Scenario Reviewed International journal

Tahera Hossain, Md Atiqur Rahman Ahad, Sozo Inoue

Sensors 20 ( 3811 ) 2 - 3 2020.07

Wearable Sensor-Based Gait Analysis for Age and Gender Estimation Reviewed International journal

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

Sensors 20 ( 2424 ) 2 - 4 2020.04

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

Sozo Inoue

61 ( 5 ) 453 - 455 2020.04

医療と介護のIoT

Sozo Inoue

48 ( 1 ) 35 - 41 2020.01

Characterizing Word Embeddings for Zero-Shot Sensor-Based Human Activity Recognition Reviewed International journal

Moe Matsuki, Paula Lago, Sozo Inoue

MDPI Sensors 19 ( 22 ) 1 - 26 2019.11

Language：English Publishing type：Research paper (scientific journal)

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

Other Link： https://doi.org/10.3390/s19225043

Human Activity Recognition using Earable Device Reviewed

Tahera Hossain, Md. Shafiqul Islam, Md Atiqur Rahman Ahad, Sozo Inoue

ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) 5 2019.09

Nurse Care Activity Recognition Challenge: Summary and Results Reviewed

Paula Lago, Sayeda Shamma Alia, Shingo Takeda, Tittaya Mairittha, Nattaya Mairittha, Farina Faiz, Yusuke Nishimura, Kohei Adachi, Tsuyoshi Okita, Franois Charpillet , Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 6 pages 2019.09

Reduction of Marker-Body Matching Work in Activity Recognition Using Motion Capture Reviewed

Shingo Takeda, Paula Lago, Tsuyoshi Okita, Sozo Inoue

International Workshop on Human Activity Sensing Corpus and Applications ７ pages 2019.09

A Dialogue-Based Annotation for Activity Recognition Reviewed

Tittaya Mairittha, Nattaya Mairittha, Sozo Inoue

International Workshop on Human Activity Sensing Corpus and Applications 6 pages 2019.09

Optimizing Activity Data Collection with Gamification Points Using Uncertainty Based Active Learning Reviewed

Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue

International Workshop on Human Activity Sensing Corpus and Applications 7 pages 2019.09

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 ) 2019.09

Evaluation of Transfer Learning for Human Activity Recognition among Different Datasets Reviewed

Md. Shafiqul Islam, Tsuyoshi Okita, Sozo Inoue

International Conference on Pervasive Intelligence and Computing (2019) (IEEE PICom 2019) 2019.08

On-Device Deep Learning Inference for Efficient Activity Data Collection Reviewed

Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue

Sensors 19 ( 15 ) 2 - 0 2019.08

A Comparative Study on Missing Data Handling Using Machine Learning for Human Activity Recognition Reviewed

Tahera Hossain, Sozo Inoue

International Conference on Activity and Behavior Computing 6 pages 2019.05

Integrating Activity Recognition and Nursing Care Records: the System, Experiment, and the Dataset Reviewed

Sozo Inoue, Tittaya Mairittha, Nattaya Mairittha, Tahera Hossain

International Conference on Activity and Behavior Computing 6 pages 2019.05

Crowdsourcing System Management for Activity Data with Mobile Sensors Reviewed

Nattaya Mairittha, Sozo Inoue

International Conference on Activity and Behavior Computing 6 pages 2019.05

Toward Projection Learning between Sensor Data and Semantic Word Vector for Zero-shot Learning Reviewed

Moe Matsuki, Sozo Inoue

International Conference on Activity and Behavior Computing 6 pages 2019.05

Comparing Feature Learning Methods for Human Activity Recognition: Performance Study in New User Scenario Reviewed

Paula Lago, Sozo Inoue

International Conference on Activity and Behavior Computing 5 pages 2019.05

Sensor-based Daily Activity Understanding in Caregiving Center Reviewed

Tahera Hossain, Sozo Inoue

IEEE PerCom Student Forum 2 pages 2019.03

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 ) 2019.02

A Hybrid Model Using Hidden Markov Chain and Logic Model for Daily Living Activity Recognition Reviewed

Paula Lago, Sozo Inoue

International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2018) 4 - 7 2018.12

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 2018.11

Activity Recognition: Translation Across Sensor Modalities Using Deep Learning

Tsuyoshi Okita, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 1462 - 1471 2018.10

Supervised and Neural Classifiers for Locomotion Analysis Reviewed

Swapnil Sayan Saha, Shafizur Rahman, Tahera Hossain, Sozo Inoue, Md Atiqur Rahman Ahad

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) 1563 - 1570 2018.10

Study of LoRaWAN Technology for Activity Recognition Reviewed

Tahera Hossain, Yusuke Doi, Tahia Tazin, Md Atiqur Rahman Ahad, Sozo Inoue

5 pages 2018.10

MEASURed: A Multi-Sensor Setting Activity Recognition Simulation Tool Reviewed

Shingo Takeda, Paula Lago, Tsuyoshi Okita, Sozo Inoue

5 pages 2018.10

FonLog - A Mobile App for Nursing Activity Recognition Reviewed

Nattaya Mairittha (Fah), Tittaya Mairittha (Fon), Sozo Inoue

4 pages 2018.10

Sensing Experiment in a Caregiving Facility for Correlation Analysis of Sleep and Daytime Activities Reviewed

Moe Matsuki, Sozo Inoue

4 pages 2018.10

Activity Recognition by Using LoRaWAN Sensor Reviewed

Tahera Hossain, Tahia Tazin, Md Atiqur Rahman Ahad, Sozo Inoue

4 pages 2018.10

Improving Sensor-based Activity Recognition Using Motion Capture as Additional Information Reviewed

Paula Lago, Shingo Takeda, Tsuyoshi Okita, Sozo Inoue

4 pages 2018.10

Pre-Consulting Dialogue Systems for Telemedicine: Yes/No Intent Classification Reviewed

Tittaya Mairittha (Fon), Tsuyoshi Okita, Sozo Inoue

4 pages 2018.10

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 Reviewed

松木萌, 井上創造, 清田陽司

情報処理学会論文誌 2018.07

Language：Japanese Publishing type：Research paper (international conference proceedings)

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 Reviewed

Norikazu Ikoma, Yusuke Doi, Sozo Inoue

6 pages 2018.06

A Study on Sensor-based Activity Recognition Having Missing Data Reviewed

Tahera Hossain, Hiroki Goto, Md Atiqur Rahman Ahad, Sozo Inoue

6 pages 2018.06

Machine Learning of User Attentions in Sensor Data Visualization Reviewed

Keita Fujino, Sozo Inoue, Tom Shibata

125 - 143 2018.03

Dialogue Breakdown Detection with Long Short Term Memory Reviewed

Tittaya Mairittha (Fon), Tsuyoshi Okita, Sozo Inoue

245 - 250 2018.03

Gamification for High-quality Dataset in Mobile Activity Recognition Reviewed

Nattaya Mairittha (Fah), Sozo Inoue

216 - 222 2018.03

Improving Activity Recognition for Missing Data Reviewed

Tahera Hossain, Hiroki Goto, Sozo Inoue

4 pages 2018.02

Towards pervasive geospatial affect perception Reviewed

22 ( 1 ) 143 - 169 2018.01

Deep Recurrent Neural Network for Mobile Human Activity Recognition with High Throughput Reviewed

Masaya Inoue, Sozo Inoue, Takeshi Nishida

1 - 13 2017.12

Recognition of Multiple Overlapping Activities Using Compositional CNN-LSTM Model Reviewed

Tsuyoshi Okita, Sozo Inoue

2017.09

Quality Requirements for Electronic Health Record Systems A Japanese-German Information Management Perspective Reviewed

A. Winter, K. Takabayashi, F. Jahn, Eizen Kimura, R. Engelbrecht, R. Haux, M. Honda, U. H. Hubner, Sozo Inoue, C. D. Kohl, T. Matsumoto, Y. Matsumura, K. Miyo, Naoki Nakashima, H. -U. Prokosch, M. Staemmler

Journal of Methods of Information in Medicine 56 92 - 104 2017.09

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}) Reviewed

峯崎智裕, 松木萌, 井上創造

情報処理学会論文誌 58 ( 10 ) 2017.07

Language：Japanese Publishing type：Research paper (scientific journal)

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 2017.06

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 2017.01

Recognizing and Understanding Nursing Activities for a Whole Day with a Big Dataset Reviewed

Sozo Inoue, Naonori Ueda, Yasunobu Nohara, Naoki Nakashima

Journal of Information Processing 24 ( 6 ) 853 - 866 2017.01

携帯センサと近接センサを用いた看護師業務分析 Reviewed

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 2017.01

Language：Japanese Publishing type：Research paper (scientific journal)

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

DICOMO2017 (Multimedia, Distributed, Cooperative, and Mobile Symposium)

INOUE Sozo, MATSUKI Moe, OKAZAKI Ai, KIYOTA Yoji

Journal of Information Processing and Management ( Japan Science and Technology Agency ) 60 ( 8 ) 603 - 607 2017.01

Supervised and Unsupervised Transfer Learning for Activity Recognition from Simple In-home Sensors Reviewed

Sozo Inoue, Xincheng Pan

International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) (Acceptance Rate: 30%) 20 - 27 2016.11

Mobile Activity Recognition from Training Labels with Inaccurate Activity Segments (Best paper candidate) Reviewed

Takamichi Toda, Sozo Inoue, Naonori Ueda

International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) (Acceptance Rate: 30%) 57 - 64 2016.11

Activity recognition and future prediction in hospitals Reviewed

28-November-2016 59 - 65 2016.11

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 2016.10

Predicting Daily Nursing Load from Nurses' Activity Logs and Patients' Medical Records Reviewed

Sozo Inoue, Tatsuya Isoda, Mako Shirouzu, Yasuhiko Sugiyama, Yasunobu Nohara, Naoki Nakashima

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 4 pages 2016.09

Recognizing Unknown Activities Using Semantic Word Vectors and Twitter Timestamps Reviewed

Moe Matsuki, Sozo Inoue

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 823 - 830 2016.09

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 2016.09

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 ) 2016.08

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 2016.08

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 ) 2016.08

Human Sensing with Wearable Sensors

INOUE Sozo

Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 28 ( 6 ) 170 - 186 2016.01

Nursing Activity Sensing Using Mobile Sensors and Proximity Sensors Reviewed

Tatsuya Isoda, Yasunobu Nohara, Sozo Inoue, Mako Shirouzu, Yasuhiko Sugiyama, Mari Hirata, Kyoko Machida, Naoki Nakashima

The 47th ISCIE International Symposium on Stochastic Systems Theory and Its Applications (SSS) 7 pages 2015.12

A Personalized Load Forecasting Enhanced by Activity Information Reviewed

Yong Ding, Sozo Inoue, Martin Alexander Neumann, Erwin Stamm, Xincheng Pan, Michael Beigl

IEEE International Smart Cities Conference (ISC2-2015) 153 - 158 2015.10

Experiment for Automatic Assessment of User-generated Tests Reviewed

Atsushi Taniguchi, Sozo Inoue

IEEE International Conference on MOOCs, Innovation and Technology in Education (MITE) 152 - 155 2015.10

Experiment for Nursing Activity Analysis Using Mobile Sensors and Proximity Sensors Reviewed

Tatsuya Isoda, Yasunobu Nohara, Sozo Inoue, Mako Shirouzu, Yasuhiko Sugiyama, Mari Hirata, Kyoko Machida, Naoki Nakashima

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 153 - 156 2015.09

A Method for Automatic Assessment of User-generated Tests and Its Evaluation Reviewed

Atsushi Taniguchi, Sozo Inoue

ACM Int'l Conf. Pervasive and Ubiquitous Computing (Ubicomp) Poster 225 - 228 2015.09

Analyzing Daily-life Activities and Power Consumptions Using Tablet Sensors and Activity Annotation Web System Reviewed

Xincheng Pan, Tomohiro Minezaki, Tatsuya Isoda, Shota Tanaka, Yuri Uchino, Sozo Inoue

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 1443 - 1452 2015.09

Finally, Ubiquitous Healthcare, in Earnest

Sozo Inoue, Naoki Nakashima

56 ( 9 ) 870 - 873 2015.09

Predictive Approaches for Low-cost Preventive Medicine Program in Developing Countries Reviewed

Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima

The 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2015.08

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 2015.01

Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study Reviewed

Yasunobu Nohara, Eiko Kai, Partha Ghosh, Rafiqul Islam Maruf, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu,Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Yukino Baba, Hisashi Kashima, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima

J Med Internet Res 16 2014.12

Evolving Health Consultancy by Predictive Caravan Health Sensing in Developing Countries Reviewed

Eiko Kai, Ashir Ahmed, Sozo Inoue, Naoki Nakashima, Masaru Kitsuregawa

ACM UbiComp International Workshop on Smart Health Systems and Applications (SmartHealthSys) 1225 - 1232 2014.09

Room Exit Recognition Using Mobile Accelerometers and Illuminometers Reviewed

Tatsuya Isoda, Sozo Inoue, Shuji Kutsuna, Masato Kawano

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 731 - 735 2014.09

Training Human Activity Recognition for Labels with Inaccurate Time Stamps Reviewed

Takamichi Toda, Sozo Inoue, Shota Tanaka, Naonori Ueda

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 863 - 872 2014.09

A Method for Tracking On-body Sensor Positions Utilizing Prior Knowledge Reviewed

Naoto Migita, Takuya Yumiyama, Sozo Inoue, Takeshi Nishida

Ubicomp Workshop for Human Activity Sensing Corpus and its Application (HASCA) 758 - 766 2014.09

A Method for Assessing User-generated Tests for Online Courses Exploiting Crowdsourcing Concept Reviewed

Ghada Farouk Naiem, Sozo Inoue

International Workshop on Web Intelligence and Smart Sensing (IWWISS) 2014.09

Applicability of Portable Health Clinic for ageing Society Reviewed

Ashir Ahmed, Andrew Robeiro-Hargrave, Rafiqul Islam Maruf, Sozo Inoue, Naoki Nakashima

International Conference on Human-Computer Interaction (HCI International), Springer LNCS 2014.06

Empowering the healthcare worker using the Portable Health Clinic Reviewed

Eiko Kai, Andrew Robeiro-Hargrave, Sozo Inoue, Yasunobu Nohara, Rafiqul Islam Maruf, Naoki Nakashima, Ashir Ahmed

The 28th IEEE International Conference on Advanced Information Networking and Applications (AINA) 759 - 764 2014.05

State estimation and control of a mobile robot using Kalman filter and particle filter Reviewed

Takeshi Nishida, Sozo Inoue, Shinichi Sagara

Proc. International Symposium on Artificial Life and Robotics 633 - 636 2014.01

Toward Measuring Fatigue by Acceleration Data in a Marathon Reviewed

Takamichi Toda, Sozo Inoue

2013 International Workshop on ICT 4 pages 2013.12

State estimation of mobile robot using GPS signal that includes reflected and diffracted waves Reviewed

Takeshi Nishida, Sozo Inoue, Shinichi Sagara

Artificial Life and Robotics 18 ( 3 ) 178 - 186 2013.12

Parallel, Distributed, and Differential Processing System for Human Activity Sensing Flows Reviewed

Takamichi Toda, Sozo Inoue, Lin Li

International Workshop on Human Activity Sensing Corpus and its Application (HASCA) at Ubicomp 1 - 1 2013.09

An Affordable, Usable and Sustainable Preventive Healthcare System for Unreached People in Bangladesh Reviewed

Naoki Nakashima, Yasunobu Nohara, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Partha Ghosh, Rafiqul Islam Maruf, Tatsuo Hiramatsu, Kunihisa Kobayashi, Toyoshi Inoguchi, Masaru Kitsuregawa

World Congress on Medical and Health Informatics (MedInfo) 105 - 1 2013.08

Portable Health Clinic Packages for BoP Reviewed

Yasunobu Nohara, Naoki Nakashima, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Partha Ghosh, Rafiqul Islam Maruf, Tatsuo Hiramatsu, Kunihisa Kobayashi, Toyoshi Inoguchi

World Congress on Medical and Health Informatics 126 - 8 2013.08

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

Sozo Inoue, Kosuke Hayashida, Masato Nakamura, Yasunobu Nohara, Naoki Nakashima

International Conference on Human-Computer Interaction (HCI International), Springer LNCS 8014 280 - 289 2013.07

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

Ashir Ahmed, Sozo Inoue, Eiko Kai, Naoki Nakashima, Yasunobu Nohara

International Conference on Human-Computer Interaction (HCI International), Springer LNCS 8028 265 - 274 2013.07

「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 2013.07

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 2013.07

GramHealth BigData for Smart Healthcare Applications Reviewed

Eiko Kai, Sozo Inoue, Ashir Ahmed

International IEEE Engineering in Medicine and Biology Society (EMBS) Conference 1 page 2013.07

GramHealth: A bottom-up approach to provide preventive healthcare services for unreached community Reviewed

Ashir Ahmed, Lutfe Kabir, Eiko Kai, Sozo Inoue

International Conference on IEEE Engineering in Medicine and Biology Society 1 page 2013.07

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 ) 2013.05

Finding Nursing in the Room from Accelerometers and Audio on Mobile Sensors Reviewed

Masato Nakamura, Sozo Inoue, Yasunobu Nohara, Naoki Nakashima

IUI Workshop on Location Awareness for Mixed and Dual Reality (LAMDa) 17 - 20 2013.03

Hierarchical Annotation Management Method for Activity Information Collecting System Reviewed

Yuichi Hattori, Shota Tanaka, Sozo Inoue

International Workshop on Network Traffic Control, Analysis and Applications (NTCAA-2012) 662 - 667 2012.11

Sensor Data Analytics to Complement Sparse and Incomplete Medical Records for Diabetes Disease Management Reviewed

Rudy Raymond, Naoki Nakashima, Yasunobu Nohara, Sozo Inoue

International Workshop on Pattern Recognition for Healthcare Analytics 5 - 8 2012.11

Large-scale Sensor Dataset in a Hospital Reviewed

Yasunobu Nohara, Sozo Inoue, Naoki Nakashima, Naonori Ueda, Masaru Kitsuregawa

International Workshop on Pattern Recognition for Healthcare Analytics 9 - 12 2012.11

Activity Sharing System with Windows Phones and Motion Data

Yuichi Hattori, Naoto Migita, Shota Tanaka, Sozo Inoue

Microsoft Research Asia Faculty Summit 1 page 2012.10

Dependency Management System with Hadoop Streaming for Data-analytic Projects Reviewed

Lin Li, Sozo Inoue

Korea-Japan Joint Workshop on ICT 4 pages 2012.09

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 2012.03

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） ) 2012.03

Language：Japanese Publishing type：Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)

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 Reviewed

Sozo Inoue, Yuichi Hattori, Yasunobu Nohara, Naoki Nakashima

Submitted to Springer 2 - 0 2012.02

Implementation of Activity Recognition From Accelerometers on Mobile Phones Reviewed

Go Hirakawa, Thin Thin Nwe, Yuichi Hattori, Sozo Inoue

3rd International Conference on Intelligent Networking and Collaborative Systems (INCoS 2011) 2 pages 2011.11

Visualization for Activity Information Sharing System Using Self-Organizing Map Reviewed

Yuichi Hattori, Sozo Inoue, Go Hirakawa

International Workshop on Network Traffic Control, Analysis and Applications (NTCAA-2011) 6 pages 2011.10

Toward High-level Activity Recognition from Accelerometers on Mobile Phones

Sozo Inoue, Yuichi Hattori

Proc. IEEE International Conference on Cyber, Physical and Social Computing (CPSCom 2011) 7 pages 2011.10

Benchmarking `Radio Exercises' Recognition with a Three-axis Accelerometer Reviewed

Akio Terumoto, Sozo Inoue, Yuichi Hattori

SMC Workshop on Robust machine learning techniques for human activity recognition 5 pages 2011.10

Challenges for Activity Recognition with Real Data Reviewed

Sozo Inoue

Ubicomp Workshop on Mobile Sensing: Challenges, Opportunities and Future Directions 2011 2 pages 2011.09

HASC2011corpus: Towards the Common Ground of Human Activity Recognition Reviewed

Nobuo Kawaguchi, Ying Yang, Tianhui Yang, Nobuhiro Ogawa, Yohei Iwasaki, Katsuhiko Kaji, Tsutomu Terada, Kazuya Murao, Sozo Inoue, Yoshihiro Kawahara, Yasuyuki Sumi, Nobuhiko Nishio

Proc. International Conference on Ubiquitous Computing (Ubicomp 2011) Poster 571 - 572 2011.09

A Large Scale Gathering System for Activity Data using Mobile Devices Reviewed

Yuichi Hattori, Sozo Inoue

Journal of Information Processing 20 ( 1 ) 177 - 184 2011.09

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 2011.08

Language：Japanese Publishing type：Article, review, commentary, editorial, etc. (other)

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 Reviewed

Yuichi Hattori, Sozo Inoue, Go Hirakawa

IEEE International Symposium on Wearable Computers (ISWC2011) 97 - 100 2011.06

Location Recognition in RFID Bookshelves Reviewed

Sozo Inoue, Yasunobu Nohara, Masaki Takemori, Kozo Sakuragawa

IEICE Transaction, Vol. E94-D ( 6 ) 1147 - 1152 2011.06

HASC Challenge: Gathering Large Scale Human Activity Corpus for the Real-World Activity Understandings Reviewed

Nobuo Kawaguchi, Nobuhiro Ogawa, Yohei Iwasaki, Katsuhiko Kaji, Tsutomu Terada, Kazuya Murao, Sozo Inoue, Yoshihiro Kawahara, Yasuyuki Sumi, Nobuhiko Nishio

Proc. Augmented Human Conference ( 27 ) 1 - 5 2011.03

Community Based Feature Database Construction for Mobile Image Retrieval

Shigeru Takano, Kensuke Baba, Sozo Inoue

Proc. IADIS e-Society 2011 (ES 2011) Conference (Poster/Demo) 580 - 582 2011.03

Activity Information Sharing System with Video and Acceleration Data Reviewed

Go Hirakawa, Yuichi Hattori, Masato Nakamura, Sozo Inoue

Proc. Int'l Conf. Pervasive and Embedded Computing and Communication Systems 557 - 561 2011.03

Gathering Large Scale Human Activity Information Using Mobile Sensor Devices Reviewed

Yuichi Hattori, Sozo Inoue, Go Hirakawa, Osamu Sudoh

Proc. International Workshop on Network Traffic Control, Analysis and Applications (NTCAA-2010) 708 - 713 2010.11

A Secure and Scalable Identification for Hash-based RFID Systems Using Updatable Pre-computation Reviewed

Yasunobu Nohara, Sozo Inoue

Proc. 3rd ACM Conf. Wireless Network Security(Wisec'10) 65 - 74 2010.03

On the Observability of RFID Data Privacy Reviewed

Sozo Inoue, Yasunobu Nohara

Proc. Int'l WS Network Traffic Control, Access, and Applications(NTCAA) 714 - 718 2009.12

An Efficient Identification and Indexing for Secure RFID with d-Left Hashing Reviewed

Yasunobu Nohara, Sozo Inoue

DBSJ Journal 8 ( 2 ) 7 - 12 2009.09

Toward Accurate Location Detection in RFID Bookshelves Reviewed

Yasunobu Nohara, Sozo Inoue, Masaki Takemori, Kozo Sakuragawa

Proc. Int'l Symp. Ubiquitous Computing Systems(UCS) 2009 99 - 104 2009.08

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 2009.07

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 2009.07

Language：Japanese Publishing type：Research paper (bulletin of university, research institution)

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

Other Link： http://ci.nii.ac.jp/naid/120001469071

Access Flows to a Repository from Other Services Reviewed

Disuke Ikeda, Sozo Inoue

Open Repositories 2009 (Poster) 4 pages 2009.05

Construction and Use Examples of Private Electronic Notary Service in Educational Institutions Reviewed

Masanori Nakakuni, Eisuke Ito, Yoshiaki Kasahara, Sozo Inoue, Hiroshi Dozono

WSEAS Transaction on Advances in Engineering Education, Issue 1, ISSN: 1790-1979 5 676 - 686 2008.11

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 2008.10

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 2008.10

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 2008.10

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 2008.10

eService Innovation and Sensor Based Healthcare

Osamu Sudoh, Sozo Inoue, Naoki Nakashima

Proc. IFIP International Federation for Information Processing, Springer Boston 286 1 - 14 2008.08

A Sustainable Model based on the Social Network Service to Support the Research Cycle Reviewed

Disuke Ikeda, Sozo Inoue

Proc. of The 3rd International Conference on Open Repositories 4 pages 2008.04

A Secure High-Speed Identification Scheme for RFID Using Bloom Filters Reviewed

Yasunobu Nohara, Sozo Inoue, Hiroto Yasuura

Proc. of 3rd International Conference on Availability, Reliability and Security (ARES) 717 - 722 2008.03

Protecting Global Medical Telemetry Infrastructure Reviewed

Benessa Defend, Mastooreh Salajegheh, Kevin Fu, Sozo Inoue

I3P White Paper 1 - 5 2008.01

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

Sozo Inoue, Disuke Ikeda

DRF Int'l Conf. 2008 5 - 8 2008.01

Trustworthy SNS for Institutional Repositories Reviewed

Sozo Inoue, Yuko Hori, Disuke Ikeda

DRF International Conference 1 page 2008.01

IR and RI: Smooth Use from External Systems Reviewed

Mayumi Ono, Sozo Inoue, Nami Hoshiko

DRF International Conference 1 page 2008.01

Toward Efficient Identification for Privacy-preserving Hash-based RFID Schemes Reviewed

Yasunobu Nohara, Sozo Inoue, Hiroto Yasuura

International Workshop on Real Field Identification 0 46 - 51 2007.11

RFID Application for Library Reviewed

Sozo Inoue, Daisuke Miyaoka, Disuke Ikeda, Toshiro Minami, Kiyotaka Fujisaki

International Workshop on Real Field Identification 0 31 - 38 2007.11

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 2007.10

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 2007.10

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 2007.10

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 2007.10

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 2007.08

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 2007.06

Unlinkability and Real World Constraints in RFID Systems Reviewed

Yasunobu Nohara, Sozo Inoue, Hiroto Yasuura

Proc. Pervasive RFID/NFC Technology and Applications Workshop 371 - 376 2007.03

RFIDを利用した救急トリアージシステムの実証実験 Reviewed

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 2007.02

Language：Japanese Publishing type：Research paper (scientific journal)

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 Reviewed

Sozo Inoue, Akihito Sonoda, Ken'ichiro Oka, Shin'ichiro Fujisaki

Proc. 1st International Conference on Pervasive Computing Technologies for Healthcare 7 pages 2006.11

Unlinkable Identification for Large-scale RFID Systems Reviewed

Yasunobu Nohara, Toru Nakamura, Kensuke Baba, Sozo Inoue, Hiroto Yasuura

IPSJ Journal 47 ( 8 ) 2362 - 2370 2006.08

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 2006.06

Systematic Error Detection for RFID Reliability Reviewed

Sozo Inoue, Daisuke Hagiwara, Hiroto Yasuura

International Conference on Availability, Reliability and Security (ARES) 280 - 286 2006.04

On Authentication between Human and Computer Reviewed

Takahiro Watanabe, Yasunobu Nohara, Kensuke Baba, Sozo Inoue

IEEE International Conference on Pervasive Computing and Communications (PerCom) Workshops 636 - 639 2006.03

Emergency Healthcare Support: RFID Based Massive Injured People Management Reviewed

Sozo Inoue, Akihito Sonoda, Ken'ichiro Oka, Shin'ichiro Fujisaki

Proc. Pervasive Healthcare Workshop in Ubicomp 2006 (UbiHealth) 9 pages 2006.01

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 2006.01

Language：Japanese Publishing type：Article, review, commentary, editorial, etc. (other)

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 Reviewed

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 2005.01

Quantitative Evaluation of Unlinkable ID Matching Schemes Reviewed

Yasunobu Nohara, Sozo Inoue, Kensuke Baba, Hiroto Yasuura

ACM Conference on Computers and Communications Security (CCS) Workshop in the Electronic Society 55 - 60 2005.01

An RFID-based Multi-service System for Supporting Conference Events Reviewed

Takahiro Watanabe, Sozo Inoue, Hiroto Yasuura, Jun Sasaki, Yasushi Aoki, Kazumi Akimoto

International Conference on Active Media Technology (AMT) 435 - 439 2005.01

Toward Unlinkable ID Management for Multi-service Environments Reviewed

Yasunobu Nohara, Sozo Inoue, Hiroto Yasuura

IEEE International Conference on Pervasive Computing and Communications (PerCom) Workshops 115 - 119 2005.01

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 2005.01

A Systematic Approach for the Reliability of RFID Systems Reviewed

Sozo Inoue, Daisuke Hagiwara, Hiroto Yasuura

IEEE TENCON 183 - 186 2004.01

Aspects of Privacy for RFID Systems

Sozo Inoue

International Workshop Series on RFID web publication 2004.01

RFID Privacy Using User-Controllable Uniqueness Reviewed

Sozo Inoue, Hiroto Yasuura

RFID Privacy Workshop Web Publication 2003.01

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 Reviewed

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 2002.01

Language：Japanese Publishing type：Research paper (scientific journal)

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．

Privacy in the Digitally Named World with RFID Tags Reviewed

Sozo Inoue, Shin'ichi Konomi, Hiroto Yasuura

Workshop on Socially-informed Design of Privacy-enhancing Solutions in UbiComp 2002 Web Publication 2002.01

Supporting Dynamic Process Specifications using Communication based Processes Reviewed

Sozo Inoue, Mizuho Iwaihara

Hawaii International Conference on System Sciences CD-ROM 2002.01

Development and Operation of a Document Database for University Research and Education Activities Reviewed

Yusuke Nonaka, Sozo Inoue, Katsuhiko Hatano, Tsutomu Harada, Yoshinari Nomura, Mizuho Iwaihara, Tsunenori Mine, Kazuwo Ushijima

Systems and Computers in Japan 33 ( 0 ) 41 - 53 2002.01

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 2002.01

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 Reviewed

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 2001.01

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 Reviewed

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 1999.01

Language：Japanese Publishing type：Research paper (scientific journal)

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 Reviewed

Sozo Inoue, Mizuho Iwaihara

International Symposium on Database Applications in Non-Traditional Environments (DANTE), IEEE Press 351 - 358 1999.01

Structured Message Management for Group Interaction Reviewed

Sozo Inoue, Mizuho Iwaihara

International Workshop on New Database Technologies for CSCW and Spatio-Temporal Data Management (NewDB) 0 398 - 407 1998.01

On Unifying Message and Transaction Management for Collaborative Design Work Reviewed

Mizuho Iwaihara, Sozo Inoue, Hiroki Matsuo

International Symposium on Digital Media Information Base (DMIB) 300 - 304 1997.01

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection Reviewed International journal

Sensors ( MDPI ) 25 ( 11 ) 3324 - 3324 2025.05

Nurse Activity Recognition in Gastrostomy Tube Feeding Using Video-Based Pose with Large Language Model-Guided Features Reviewed International journal

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 28 2025.05

Domain Knowledge Integration with Chain of Thought and Knowledge Prompting in Text to Motion Generation Reviewed International journal

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 25 2025.05

Extraction and Summarization from Visiting Nurse Transcriptions Using Improved Prompt Techniques Reviewed International journal

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 50 2025.05

Summary of the Virtual Data Generation for Complex Industrial Activity Recognition Reviewed International journal

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 2 ) 1 - 12 2025.05

Toward Abnormal Activity Recognition of Developmentally Disabled Individuals Using Pose Estimation Reviewed International journal

International Journal of Activity and Behavior Computing ( Care XDX Center, Kyushu Institute of Technology ) 2025 ( 1 ) 1 - 28 2025.05

Advancing Heatstroke Prevention: Integrating Physiological Data for Enhanced Thermal Comfort Forecasting Reviewed International journal

Activity, Behavior, and Healthcare Computing ( CRC Press ) 257 - 274 2025.02

Toward Detecting and Explaining Stress of Nurses Using Wearable Devices and LLMs Reviewed International journal

International Conference on Ubiquitous Computing and Ambient Intelligence ( Springer Nature Switzerland Cham ) 288 - 299 2024.11

Preliminary Investigation of Activity Prediction in Nursing Homes using Activity History with Erroneous Time Stamps Reviewed International journal

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 851 - 855 2024.10

Synthetic Skeleton Data Generation using Large Language Model for Nurse Activity Recognition Reviewed International journal

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 493 - 499 2024.10

A Monocular Fisheye Video-Based 2D to 3D Pose Lift Technique with Multiperson Spatial Context Integration Reviewed International journal

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 475 - 480 2024.10

Large Language Models for Generating Semantic Nursing Activity Logs: Exploiting Temporal and Contextual Information Reviewed International journal

Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing 481 - 486 2024.10

Elderly Motion Analysis to Estimate Emotion: A Systematic Review Reviewed International journal

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

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 23 2024.06

Nurses' Skill Assessment in Endotracheal Suctioning Using Video-based Activity Recognition Reviewed International journal

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 2024.06

Integrating Human Behavioral Model for Safe Intimate-distance Human Robot Collaboration Reviewed International journal

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 2024.06

Leveraging the Large Language Model for Activity Recognition: A Comprehensive Review Reviewed International journal

Milyun Ni’ma Shoumi, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 27 2024.06

Toward Extracting Care Records from Transcriptions of Visiting Nurses Using Large Language Models Reviewed International journal

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

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 17 2024.06

Improving Fatigue Detection with Feature Engineering on Physical Activity Accelerometer Data Using Large Language Models Reviewed International journal

Elsen Ronando, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 2 ) 1 - 22 2024.06

Toward Recognizing Nursing Activity in Endotracheal Suctioning Using Video-based Pose Estimation Reviewed International journal

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 2024.05

Synchronizing an AR Robot Simulator with a Real Industrial Robot Reviewed International journal

Naoya Ryoke, Nazmun Nahid, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 20 2024.05

Forecasting Sit-to-Stand Transitions in Wheelchair Patients: a Textile Pressure Sensor-based Approach Reviewed International journal

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

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 20 2024.05

Evaluation of Functional Estimation Methods in IoT Devices at Intervals of a Few Seconds by Communication Traffic Analysis Reviewed International journal

Yuichi Hattori, Yutaka Arakawa, Sozo Inoue

International Journal of Activity and Behavior Computing ( Care XDX Center ) 2024 ( 1 ) 1 - 19 2024.05

A Relabeling Approach to Signal Patterns for Beacon-based Indoor Localization in Nursing Care Facility Reviewed International journal

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 2024.05

Improved Evaluation Metrics for Sentence Suggestions in Nursing and Elderly Care Record Applications Reviewed International journal

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

Healthcare ( MDPI ) 12 ( 3 ) 367 2024.01

Relabeling for Indoor Localization Using Stationary Beacons in Nursing Care Facilities Reviewed International journal

Christina Garcia, Sozo Inoue

Sensors ( MDPI ) 24 ( 2 ) 319 2024.01

Estimate of Cat Excretion Information Using Multiple Weight Sensors Reviewed International journal

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 ) 2023.10

Toward Pioneering Sensors and Features Using Large Language Models in Human Activity Recognition Reviewed International journal

Haru Kaneko, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) ( ACM ) 2023.10

Predicting and Analyzing Emotion of Elderly People in Care Facilities Reviewed International journal

Xinyi Min, Haru Kaneko, Sozo Inoue

Ubicomp Workshop on Human Activity Sensing Corpus and Applications (HASCA) ( ACM ) 457 - 462 2023.10

Function-level Access Control System for Home IoT Devices Reviewed International journal

Yuichi Hattori, Yutaka Aarakawa, Daichi Koike, Shigemi Ishida, Sozo Inoue

Sensors and Materials 34 ( 6 ) 2125 - 2139 2022.06

Toward the Analysis of Office Workers’ Mental Indicators Based on Wearable, Work Activity, and Weather Data Reviewed International journal

Yusuke Nishimura, Tahera Hossain, Akane Sano, Shota Isomura, Yutaka Aarakawa, Sozo Inoue

International Conference on Activity and Behavior Computing (ABC) 1 - 26 2021.10

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