安全与环境工程2024，Vol.31Issue(4)：11-19,36,10.DOI:10.13578/j.cnki.issn.1671-1556.20221657
基于可穿戴惯性传感技术的人体步态阶段识别
Human gait phase recognition based on wearable inertial sensing technology
摘要
Abstract
In order to realize recognition of human gait phases based on wearable inertial sensing technolo-gy,the human gait phase recognition models based on feature selection,time proportion optimization,and machine learning with multiple data types,multiple features,and multiple classifiers were developed to rec-ognize the human gait phases,and the recognition effect of the three models are compared.The results show that the average accuracy of human gait phase recognition based on feature selection is 73.66％,on time proportion optimization is 90.96％,and on machine learning models trained with pedal pitch angle data and acceleration data is 97.04％and 86.80％,respectively.Different recognition methods can be selectively used according to different human gait phases and application scenarios to achieve desired recognition effects.The comprehensive use of time proportion optimization algorithm and machine learning methods can achieve high comprehensive recognition accuracy.The paper provides a reference for further research on human behavior based on wearable sensors.关键词
人体步态阶段识别/可穿戴惯性传感技术/特征选择/时间比例优化/机器学习Key words
human gait phase recognition/wearable inertial sensing technology/feature selection/time pro-portion optimization/machine learning分类
资源环境引用本文复制引用
陈斯琪,寇俊辉,陈小路,吴铭渝,付国荣,郭良杰..基于可穿戴惯性传感技术的人体步态阶段识别[J].安全与环境工程,2024,31(4):11-19,36,10.基金项目
湖北省安全生产专项资金科技项目(SJZX20230904) （SJZX20230904）
武汉市科技局知识创新专项曙光计划项目(2022020801020209) （2022020801020209）
中央高校基本科研业务费专项资金项目 （）
