慣性センサを用いた空手動作の質的評価が可能なデジタルジャッジの開発
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| Published in | 日本機械学会論文集 Vol. 86; no. 892; p. 20-00308 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | Japanese |
| Published |
一般社団法人 日本機械学会
2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2187-9761 |
| DOI | 10.1299/transjsme.20-00308 |
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| Author | 佐武, 陸史 岩田, 浩康 相原, 伸平 石部, 開 |
|---|---|
| Author_xml | – sequence: 1 fullname: 岩田, 浩康 organization: 早稲田大学 理工学術院 – sequence: 1 fullname: 佐武, 陸史 organization: 早稲田大学 創造理工学研究科 – sequence: 1 fullname: 石部, 開 organization: 早稲田大学 創造理工学研究科 – sequence: 1 fullname: 相原, 伸平 organization: 国立スポーツ科学センター |
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| References | De Brabandere, B. A., Emmerzaal, J., Timmermans, A., Jonkers, I., Vanwanseele, B. and Davis, J., A machine learning approach to estimate hip and knee joint loading using a mobile phone-embedded IMU, Frontiers in Bioengineering and Biotechnology, Vol.8 (2020), 320. Imai, K. and Ueda, E., Motion analysis based on win/loss judgment in KARATE Kata competition, Proceedings of the Robotics and Mechatronics Conference 2017 (2017), 1P2-L02 (in Japanese). Chardonnens, J., Favre, J., Cuendet, F., Gremion, G. and Aminian, K., A system to measure the kinematics during the entire ski jump sequence using inertial sensors, Journal of biomechanics, Vol.46, No.1 (2013), pp.56–62. Siska, L., Brodáni, J., Stefanovský, M. and Todorov, S., Basic reliability parameters of a boxing punch, Journal of Physical Education and Sport, Vol.16, No.1 (2016), pp.241–244. Takano, K. and Li, K. F., A multimedia tennis instruction system: Tracking and classifying swing motions, Journal of Space-Based and Situated Computing, Vol.6, No.3 (2013), pp.155–168. Zhang, Y., Chen, K. and Yi, J., Rider trunk and bicycle pose estimation with fusion of force/inertial sensors, IEEE Transactions on Biomedical engineering, Vol.60, No.9 (2013), pp.2541–2551. McGinnis, R. S. and Perkins, N. C., A highly miniaturized, wireless inertial measurement unit for characterizing the dynamics of pitched baseballs and softballs, Sensors, Vol.12, No.9 (2012), pp.11933–11945. Adesida, Y., Enrica, P. and Alison, H. M., Exploring the role of wearable technology in sport kinematics and kinetics: A systematic review, Sensors, Vol.19, No.7 (2019), 1597. Bao, L. and Intille, S. S., Activity recognition from user-annotated acceleration data, In International conference on pervasive computing, Springer, Berlin, Heidelberg (2004), pp.1-17. Egawa, M., Theoretical consideration on punching and kicking in Karate, Japanese Academy of Budo, Vol.4, No.1 (1971), pp.35-35 (in Japanese). Masui, S., Tezuka, K. and Sasaki, K., Changing sports activities by 3D sensing technology, The journal of the Institute of Electronics, Information and Communication Engineers, Vol.100, No.11 (2017), pp.1182-1188 (in Japanese). Aihara, S., Hayashi, A., Takada, R. and Iwata, H., Development of a machine learning method to evaluate Karate skills, Proceedings of the 19th SICE System Integration Division Annual Conference (2018), 1D2-04 (in Japanese). Cust, E. E., Sweeting, A. J., Ball, K. and Robertson, S., Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance, Journal of sports sciences, Vol.37, No.5 (2019), pp.568-600. Michihara, S. and En, Y., Study on technology of Karate, Japanese Academy of Budo, Vol.11, No.1 (1978), pp.23-30 (in Japanese). Ravi, N., Dandekar, N., Mysore, P. and Littman, M. L., Activity recognition from accelerometer data. In Proceedings of the 17th conference on Innovative applications of artificial intelligence, Vol. 5, No. 2005 (2005), pp.1541-1546. Díaz-Uriarte, R. and De Andres, S. A., Gene selection and classification of microarray data using random forest, BMC bioinformatics, Vol.7, No.1 (2006), 3. Omae, Y., Kobayashi, M., Sakai, K., Akiduki, T., Shionoya, A. and Takahashi, H., Detection of swimming stroke start timing by deep learning from an inertial sensor, ICIC express letters. Part B, Applications: an international journal of research and surveys, Vol.11, No.3 (2020), pp.245-251. Sbriccoli, P., Camomilla, V., Di Mario, A., Quinzi, F., Figura, F. and Felici, F., Neuromuscular control adaptations in elite athletes: The case of top level karateka, European journal of applied physiology, Vol.108, No.10 (2010), pp.1269–1280. Mattes, K. and Schaffert, N., New measuring and on water coaching device for rowing, Journal of Human Sport and Exercise, Vol.5, No.2 (2010), pp.226–239. King, K., Hough, J., McGinnis, R. and Perkins, N. C., A new technology for resolving the dynamics of a swinging bat, Sports Engineering, Vol.15, No.1 (2012), pp.41–52. Camomilla, V., Bergamini, E., Fantozzi, S. and Vannozzi, G., Trends supporting the in-field use of wearable inertial sensors for sport performance evaluation: A systematic review, Sensors, Vol.18, No.3 (2018), 873. Morris, D., Saponas, T. S., Guillory, A. and Kelner, I., RecoFit: using a wearable sensor to find, recognize, and count repetitive exercises, In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2014), pp. 3225-3234. |
| References_xml | – reference: Egawa, M., Theoretical consideration on punching and kicking in Karate, Japanese Academy of Budo, Vol.4, No.1 (1971), pp.35-35 (in Japanese). – reference: Imai, K. and Ueda, E., Motion analysis based on win/loss judgment in KARATE Kata competition, Proceedings of the Robotics and Mechatronics Conference 2017 (2017), 1P2-L02 (in Japanese). – reference: Camomilla, V., Bergamini, E., Fantozzi, S. and Vannozzi, G., Trends supporting the in-field use of wearable inertial sensors for sport performance evaluation: A systematic review, Sensors, Vol.18, No.3 (2018), 873. – reference: Masui, S., Tezuka, K. and Sasaki, K., Changing sports activities by 3D sensing technology, The journal of the Institute of Electronics, Information and Communication Engineers, Vol.100, No.11 (2017), pp.1182-1188 (in Japanese). – reference: Morris, D., Saponas, T. S., Guillory, A. and Kelner, I., RecoFit: using a wearable sensor to find, recognize, and count repetitive exercises, In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2014), pp. 3225-3234. – reference: Omae, Y., Kobayashi, M., Sakai, K., Akiduki, T., Shionoya, A. and Takahashi, H., Detection of swimming stroke start timing by deep learning from an inertial sensor, ICIC express letters. Part B, Applications: an international journal of research and surveys, Vol.11, No.3 (2020), pp.245-251. – reference: Mattes, K. and Schaffert, N., New measuring and on water coaching device for rowing, Journal of Human Sport and Exercise, Vol.5, No.2 (2010), pp.226–239. – reference: Bao, L. and Intille, S. S., Activity recognition from user-annotated acceleration data, In International conference on pervasive computing, Springer, Berlin, Heidelberg (2004), pp.1-17. – reference: De Brabandere, B. A., Emmerzaal, J., Timmermans, A., Jonkers, I., Vanwanseele, B. and Davis, J., A machine learning approach to estimate hip and knee joint loading using a mobile phone-embedded IMU, Frontiers in Bioengineering and Biotechnology, Vol.8 (2020), 320. – reference: Chardonnens, J., Favre, J., Cuendet, F., Gremion, G. and Aminian, K., A system to measure the kinematics during the entire ski jump sequence using inertial sensors, Journal of biomechanics, Vol.46, No.1 (2013), pp.56–62. – reference: Ravi, N., Dandekar, N., Mysore, P. and Littman, M. L., Activity recognition from accelerometer data. In Proceedings of the 17th conference on Innovative applications of artificial intelligence, Vol. 5, No. 2005 (2005), pp.1541-1546. – reference: Zhang, Y., Chen, K. and Yi, J., Rider trunk and bicycle pose estimation with fusion of force/inertial sensors, IEEE Transactions on Biomedical engineering, Vol.60, No.9 (2013), pp.2541–2551. – reference: McGinnis, R. S. and Perkins, N. C., A highly miniaturized, wireless inertial measurement unit for characterizing the dynamics of pitched baseballs and softballs, Sensors, Vol.12, No.9 (2012), pp.11933–11945. – reference: Cust, E. E., Sweeting, A. J., Ball, K. and Robertson, S., Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance, Journal of sports sciences, Vol.37, No.5 (2019), pp.568-600. – reference: Takano, K. and Li, K. F., A multimedia tennis instruction system: Tracking and classifying swing motions, Journal of Space-Based and Situated Computing, Vol.6, No.3 (2013), pp.155–168. – reference: Aihara, S., Hayashi, A., Takada, R. and Iwata, H., Development of a machine learning method to evaluate Karate skills, Proceedings of the 19th SICE System Integration Division Annual Conference (2018), 1D2-04 (in Japanese). – reference: Díaz-Uriarte, R. and De Andres, S. A., Gene selection and classification of microarray data using random forest, BMC bioinformatics, Vol.7, No.1 (2006), 3. – reference: King, K., Hough, J., McGinnis, R. and Perkins, N. C., A new technology for resolving the dynamics of a swinging bat, Sports Engineering, Vol.15, No.1 (2012), pp.41–52. – reference: Michihara, S. and En, Y., Study on technology of Karate, Japanese Academy of Budo, Vol.11, No.1 (1978), pp.23-30 (in Japanese). – reference: Adesida, Y., Enrica, P. and Alison, H. M., Exploring the role of wearable technology in sport kinematics and kinetics: A systematic review, Sensors, Vol.19, No.7 (2019), 1597. – reference: Siska, L., Brodáni, J., Stefanovský, M. and Todorov, S., Basic reliability parameters of a boxing punch, Journal of Physical Education and Sport, Vol.16, No.1 (2016), pp.241–244. – reference: Sbriccoli, P., Camomilla, V., Di Mario, A., Quinzi, F., Figura, F. and Felici, F., Neuromuscular control adaptations in elite athletes: The case of top level karateka, European journal of applied physiology, Vol.108, No.10 (2010), pp.1269–1280. |
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| Title | 慣性センサを用いた空手動作の質的評価が可能なデジタルジャッジの開発 |
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