Human Motion Recognition by Textile Sensors Based on Machine Learning Algorithms.
Wearable sensors for human physiological monitoring have attracted tremendous interest from researchers in recent years. However, most of the research involved simple trials without any significant analytical algorithms. This study provides a way of recognizing human motion by combining textile stretch sensors based on single-walled carbon nanotubes (SWCNTs) and spandex fabric (PET/SP) and machine learning algorithms in a realistic application. In the study, the performance of the system will be evaluated by identification rate and accuracy of the motion standardized. This research aims to provide a realistic motion sensing wearable product without unnecessary heavy and uncomfortable electronic devices.
['Vu|Chi Cuong|CC|0000-0002-7158-8441', 'Kim|Jooyong|J|0000-0003-1969-5730']
D000328:Adult D006801:Humans D000069550:Machine Learning D008297:Male D009068:Movement D037742:Nanotubes, Carbon D013784:Textiles D000076251:Wearable Electronic Devices
textiles machine learning algorithm wearables SWCNT human motion monitoring