Department of Organic Materials and Fiber Engineering, Soongsil University, Seoul 156-743, Korea.
Sensors (Basel). 2018 Sep 14;18(9):3109. doi: 10.3390/s18093109.
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.
近年来，用于人体生理监测的可穿戴传感器引起了研究人员的极大兴趣。然而，大多数研究都只是简单的试验，没有任何重要的分析算法。本研究提供了一种在实际应用中结合基于单壁碳纳米管（SWCNT）和氨纶织物（PET/SP）的纺织拉伸传感器以及机器学习算法来识别人体运动的方法。在研究中，将通过标准化运动的识别率和准确率来评估系统的性能。本研究旨在提供一种无需使用不必要的沉重和不舒适的电子设备的现实运动感测可穿戴产品。
