研究者詳細 - 和田　親宗

論文 - 和田　親宗

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Feature Selection via Decision Tree in Foot Position Recognition during Patient Transfer using Smartphone Inertial Sensor 査読有り国際誌

Kodai Kitagawa, Ryo Takashima, Tadateru Kurosawa, Chikamune Wada

SICE Festival 2024 with Annual Conference (SICE2024) WeBT11.21 2024年08月

Effects of electrical stimulation of antagonist muscles on shoulder joint adduction force and grip strength 査読有り国際誌

Nakano Sota, Okada Hirotaka, Nakamura Kouichi, Kitagawa Kodai, Wada Chikamune

Journal of Physical Therapy Science ( 理学療法科学学会 ) 36 ( 7 ) 378 - 381 2024年07月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

[Purpose] This study aimed to determine whether applying electrical stimulation to the deltoid and extensor digitorum muscles could lead to a reduction in fixation force during shoulder joint adduction and grip strength. [Participants and Methods] Fifteen healthy adult males participated in this study. In the shoulder adduction force experiment, the middle fibers of the deltoid muscle of the dominant arm were electrically stimulated. In the grip strength experiment, the extensor digitorum muscle of the dominant arm was electrically stimulated. The forces exerted with and without the electrical stimulation were measured. [Results] The torque of the shoulder adduction force decreased significantly with electrical stimulation, while no significant change was observed in normalized grip strength with electrical stimulation. [Conclusion] The response of antagonist muscles to electrical stimulation varied according to location.

DOI： 10.1589/jpts.36.378

CiNii Research

その他リンク： https://www.jstage.jst.go.jp/article/jpts/36/7/36_2024-018/_pdf

Inducing unstable walking conditions through visual and auditory stimuli 査読有り国際誌

Tomomasa Ohara, Chong Yu Zheng(UTAR), Shinji Murata, Chikamune Wada

J. Phys. Ther. Sci. 36 330 - 336 2024年06月

Foot Position Recognition Using a Smartphone Inertial Sensor in Patient Transfer 査読有り国際誌

Kodai Kitagawa, Ryo Takashima, Tadateru Kurosawa, Chikamune Wada

BioMed 4 ( 2 ) 112 - 121 2024年04月

Human Detection and Human Pose Classification for Mobile Robots Interaction 査読有り国際誌

K. Hirunthakingpunt, D. Dawan, C. Wada, N. Maneerung

2024 1st International Conference on Robotics, Engineering, Science, and Technology (RESTCON) 1 - 6 2024年02月

Enhancing Bus Number Detection Efficiency with Transfer Learning and Fine-Tuned Optical Character Recognition 査読有り国際誌

R. Arifando, S. Eto, C. Wada

2024 1st International Conference on Robotics, Engineering, Science, and Technology (RESTCON) 106 - 111 2024年02月

Deciphering pixel insights: A deep dive into deep learning strategies for enhanced indoor depth estimation 査読有り国際誌

Krisna Pinasthika, Fitri Utaminingrum(Brawijaya Univ), Chih‑Yang Lin, Chikamune Wada, Timothy K. Shih

International Journal of Information Management Data Insights 4 ( 1 ) 2024年02月

Foot Clearance Prediction using Wrist Acceleration and Gait Speed 査読有り国際誌

Kodai Kitagawa, Chikamune Wada, Nobuyuki Toya

Journal of Electronics, Electromedical Engineering, and Medical Informatics 6 ( 1 ) 32 - 39 2024年01月

Convolutional Neural Network Based Zebra Crossing and Pedestrian Traffic Light Recognition 査読有り国際誌

Shinji Eto, Yasuhiro Wada, Chikamune Wada

Journal of Mechanical and Electrical Intelligent System 6 ( 3 ) 1 - 11 2023年12月

Investigation of factors influencing low physical activity levels in community-dwelling older adults with chronic pain: a cross-sectional study 査読有り国際誌

Hida M., Imai R., Nakamura M., Nakao H., Kitagawa K., Wada C., Eto S., Takeda M., Imaoka M.

Scientific Reports 13 ( 1 ) 2023年12月

記述言語：英語掲載種別：研究論文（学術雑誌）

Low levels of physical activity in individuals with chronic pain can lead to additional functional impairment and disability. This study aims to investigate the predictors of low physical activity levels in individuals with chronic pain, and to determine the accuracy of the artificial neural network used to analyze these predictors. Community-dwelling older adults with chronic pain (n = 103) were surveyed for their physical activity levels and classified into low, moderate, or high physical activity level groups. Chronic pain-related measurements, physical function assessment, and clinical history, which all influence physical activity, were also taken at the same time. Logistic regression analysis and analysis of multilayer perceptron, an artificial neural network algorithm, were performed. Both analyses revealed that history of falls was a predictor of low levels of physical activity in community-dwelling older adults. Multilayer perceptron analysis was shown to have excellent accuracy. Our results emphasize the importance of fall prevention in improving the physical activity levels of community-dwelling older adults with chronic pain. Future cross-sectional studies should compare multiple analysis methods to show results with improved accuracy.

DOI： 10.1038/s41598-023-41319-7

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85168959895&origin=inward

Preliminary Study of Stereophonic Sound-based Electric Travel Aid for the Visually Impaired 査読有り国際誌

Shinji Eto, Hinami Sakai Wada, Chikamune Wada

11th International Symposium on Applied Engineering and Sciences (SAES2023) ID229 2023年11月

Induction of unstable walk using visual stimulation 査読有り国際誌

Tomomasa Ohara, Chong Yu Zheng(UTAR), Chikamune Wada

11th International Symposium on Applied Engineering and Sciences (SAES2023) ID195 2023年11月

Effects of Foot Placements on Lumbar Loads in Patient Transfer Motion: Comparison Between Anteroposterior and Mediolateral Placements 査読有り国際誌

Kodai Kitagawa, Hayato Nodagashira, Tadateru Kurosawa, Hinako Maeyama, Chikamune Wada

2023 IEEE 12th Global Conference on Consumer Electronics (IEEE GCCE 2023) 257 - 258 2023年10月

Comparison of Regression Models for Foot Position Prediction during Patient Lifting Motion using a Single Inertial Sensor 査読有り国際誌

Kodai Kitagawa, Chikamune Wada, Takayuki Nagasaki, Sota Nakano, Mitsumasa Hida, Shogo Okamatsu

SICE Annual Conference 2023 (SICE2023) FrPOS2.19 2023年09月

Staggering Gait Detection Method using Wrist Acceleration 査読有り国際誌

Nobuyuki Toya, Kodai Kitagawa, Chikamune Wada

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC2023) No.2549 2023年08月

Development of a Robotic Hand Glove System for Secure Grasp with AI Wireless Sensor Data 査読有り

Almassri A., Koyanagi K., Wada C., Horio K., Hasan W.Z.W.(UPM)

2023 IEEE International Conference on Mechatronics and Automation, ICMA 2023 669 - 674 2023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）

Robotic Hand glove is one of the most commonly used technique in the rehabilitation systems. In this paper, we developed a robotic hand system with a proposed sensing mechanism-based AI algorithm, which can acquire grasping forces from human fingers. It is composed of five low-cost force sensors attached to the glove's fingertips and wireless data logger. Several experiments including grasping a plastic bottle and squeezing a tennis ball are implemented to verify the efficiency of the proposed system using the developed glove. As a result, it accurately estimates the forces applied by each finger with the aim of achieving a secure grasp comparison with conventional methods.

DOI： 10.1109/ICMA57826.2023.10215914

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85170821953&origin=inward

変形性膝関節症患者の立ち上がり動作時の関節角度に対する膝装具の効果査読有り

山本裕晃, 岡松将吾, 北川広大, 和田親宗

日本義肢装具学会誌 ( 日本義肢装具学会 ) 39 ( 3 ) 219 - 224 2023年07月

担当区分：最終著者記述言語：日本語掲載種別：研究論文（学術雑誌）

軟性膝装具の装着圧力の変化が，変形性膝関節症患者の立ち上がり動作に与える影響を調べた．対象は，変形性膝関節症患者7名とした．異なる装着圧力の軟性膝装具を使用し，立ち上がり動作離殿時の膝関節屈曲角度を分析した．立ち上がり動作離殿時の膝関節屈曲角度は，Control条件と比較してHigh Pressure条件にて有意に大きくなり，装着圧力を高くすることにより増加傾向を示した．軟性膝装具の装着圧力を高くすることにより，立ち上がり動作離殿時の膝関節屈曲角度が大きくなり，効率的な立ち上がり動作が遂行できることが明らかとなった．

DOI： 10.11267/jspo.39.219

CiNii Research

Method for improving GPS high-positioning using microwave absorbers for walking movement support 査読有り国際誌

Takashi ASAKAWA, Haruka MATOBA, Daiki HORIMOTO, Chikamune WADA

Mechanical Engineering Letters ( The Japan Society of Mechanical Engineers ) 9 ( 0 ) 23-00125 - 23-00125 23-00125 2023年05月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

This paper describes a method to eliminate multipath effects by using the shield cover of a microwave absorber to improve Global Positioning System (GPS) positioning accuracy. We studied a walking movement support system for visually impaired people. The system provides audio guidance regarding the direction of movement and pedestrian signals based on the location of the intersection and the pedestrian’s GPS position. Because a pedestrian device is a wearable terminal, we want to obtain highly accurate location information with a simple mechanism that can be comfortably worn on the body. In this study, we propose a method using a shielding cover with a microwave absorber to improve the GPS positioning accuracy in environments where multipath, a major cause of positioning error, occurs. This method does not require any modification to the hardware or software of the GPS receiver, and the multipath is prevented by adjusting only the height and position of the shielding cover. In a walking experiment using the proposed method, we confirmed that the shielding plate, set at an open angle of 90 degrees, can provide positioning without being affected by multipath in an environment where there are buildings on both sides of the path.

DOI： 10.1299/mel.23-00125

CiNii Research

その他リンク： https://www.jstage.jst.go.jp/article/mel/9/0/9_23-00125/_pdf

Development of Hallux Valgus Classification Using Digital Foot Images with Machine Learning 査読有り国際誌

Mitsumasa Hida, Shinji Eto, Chikamune Wada, Kodai Kitagawa, Masakazu Imaoka, Misa Nakamura, Ryota Imai, Takanari Kubo, Takao Inoue, Keiko Sakai, Junya Orui, Fumie Tazaki, Masatoshi Takeda, Ayuna Hasegawa, Kota Yamasaka, Hidetoshi Nakao

Life 2023 13 ( 5 ) 1146 2023年05月

記述言語：英語掲載種別：研究論文（学術雑誌）

Hallux valgus, a frequently seen foot deformity, requires early detection to prevent it from becoming more severe. It is a medical economic problem, so a means of quickly distinguishing it would be helpful. We designed and investigated the accuracy of an early version of a tool for screening hallux valgus using machine learning. The tool would ascertain whether patients had hallux valgus by analyzing pictures of their feet. In this study, 507 images of feet were used for machine learning. Image preprocessing was conducted using the comparatively simple pattern A (rescaling, angle adjustment, and trimming) and slightly more complicated pattern B (same, plus vertical flip, binary formatting, and edge emphasis). This study used the VGG16 convolutional neural network. Pattern B machine learning was more accurate than pattern A. In our early model, Pattern A achieved 0.62 for accuracy, 0.56 for precision, 0.94 for recall, and 0.71 for F1 score. As for Pattern B, the scores were 0.79, 0.77, 0.96, and 0.86, respectively. Machine learning was sufficiently accurate to distinguish foot images between feet with hallux valgus and normal feet. With further refinement, this tool could be used for the easy screening of hallux valgus.

DOI： 10.3390/life13051146

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85160279187&origin=inward

Improved YOLOv5-Based Lightweight Object Detection Algorithm for People with Visual Impairment to Detect Buses 査読有り国際誌

Rio Arifando, Shinji Eto, Chikamune Wada

Appl. Sci. 2023 13 ( 9 ) 5802 2023年05月

担当区分：最終著者記述言語：英語掲載種別：研究論文（学術雑誌）

Object detection is crucial for individuals with visual impairment, especially when waiting for a bus. In this study, we propose a lightweight and highly accurate bus detection model based on an improved version of the YOLOv5 model. We propose integrating the GhostConv and C3Ghost Modules into the YOLOv5 network to reduce the number of parameters and floating-point operations per second (FLOPs), ensuring detection accuracy while reducing the model parameters. Following that, we added the SimSPPF module to replace the SPPF in the YOLOv5 backbone for increased computational efficiency and accurate object detection capabilities. Finally, we developed a Slim scale detection model by modifying the original YOLOv5 structure in order to make the model more efficient and faster, which is critical for real-time object detection applications. According to the experimental results, the Improved-YOLOv5 outperforms the original YOLOv5 in terms of the precision, recall, and mAP@0.5. Further analysis of the model complexity reveals that the Improved-YOLOv5 is more efficient due to fewer FLOPS, with fewer parameters, less memory usage, and faster inference time capabilities. The proposed model is smaller and more feasible to implement in resource-constrained mobile devices and a promising option for bus detection systems.

DOI： 10.3390/app13095802

Scopus

その他リンク： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85159346654&origin=inward

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