基于多传感器的人体运动模式识别

Human motion modes recognition based on multi-sensors

针对日常生活中人体的运动具有准周期特性的特点,设计了一种基于加速度信息与脚底压力的下肢运动信息采集系统。通过采集脚底压力信息监测关键步态事件,在事件前后对下肢加速度数据进行特征提取,从而对4种常见行为(走路、跑步、上楼和下楼)进行识别。实验结果表明:提出的方法在仅提取较为简单的时域特征信息情况下,平均识别正确率为94. 79%。

Aiming at characteristic of quasi-periodic that motion of human body has in daily life,a motion information collection system of lower limbs which is used for collecting acceleration and foot bottom pressure is designed. Acceleration data features are extracted prior to and immediately after gait events to recognize four motion modes including walking,running,stair ascent,stair descent. Experimental result shows that the average recognition accuracy is 94. 79 %,while only extracting simple time-domain features information classification.