Center for Robotics Research, Korea Institute of Science and Technology, Seoul 02792, Korea.
School of Electrical Engineering, Korea University, Seoul 02841, Korea.
Sensors (Basel). 2018 Feb 5;18(2):468. doi: 10.3390/s18020468.
Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.
大多数运动识别研究都需要紧身衣来进行精确的感应。然而，紧身衣系统很难适应实际应用，因为人们通常穿着宽松的衣服。在本文中，我们提出了一种在宽松衣物中使用灵活的压电传感器的步态识别系统。该步态识别系统并不直接感知下身角度。然而，它确实检测到站立和行走之间的转换。具体来说，我们使用附在宽松裤子的膝盖和臀部的柔性传感器的信号。我们使用行走过程中信号的离散时间傅里叶级数来检测周期性运动分量。我们将步态检测方法应用于实时的患者运动和姿势监测系统。在监测系统中，步态识别运行良好。最后，我们用 10 个受试者对步态识别系统进行了测试，该系统成功地检测到了行走，成功率超过 93%。
