Visualization of Features in Multivariate Gait Data: Use of a Deep Learning for the Visualization of Body Parts and Their Timing During Gait Training

Yusuke Osawa, Keiichi Watanuki, Kazunori Kaede, Keiichi Muramatsu. Visualization of Features in Multivariate Gait Data: Use of a Deep Learning for the Visualization of Body Parts and Their Timing During Gait Training. In Giuseppe Di Bucchianico, Cliff Sungsoo Shin, Scott Shim, Shuichi Fukuda, Gianni Montagna, Cristina Carvalho, editors, Advances in Industrial Design - Proceedings of the AHFE 2020 Virtual Conferences on Design for Inclusion, Affective and Pleasurable Design, Interdisciplinary Practice in Industrial Design, Kansei Engineering, and Human Factors for Apparel and Textile Engineering, July 16-20, 2020, USA. Volume 1202 of Advances in Intelligent Systems and Computing, pages 1007-1013, Springer, 2020. [doi]

Authors

Yusuke Osawa

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Keiichi Watanuki

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Kazunori Kaede

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Keiichi Muramatsu

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