基于表面肌电信号改进步长估计模型的个人定位方法

Personal positioning method based on the step length estimation model improved by the surface EMG signal

针对个人室内定位中步长估计方法存在估计精度不高、适用范围有限的问题,提出一种采用表面肌电信号和加速度信息的改进步长估计模型。通过采集行人在行走过程中的表面肌电信号和加速度信息,利用平滑滤波算法对该信号进行预处理,并通过峰值检测算法进行步数检测,在此基础上提出一种改进的步长估计模型,利用该模型进行了个人室内定位测试。实验测试结果表明:改进的步长估计模型可实现个人室内不同行走速度下的步长估计,该模型获得的步长估计平均误差和误差率分别为0.01 m和1.01%,个人室内定位行进距离的平均误差和误差率分别为0.78 m和0.48%,满足个人室内定位用步长估计的要求,可为康复医疗、商场购物等个人室内定位应用领域提供参考。

Aiming at the problems of low estimation accuracy and limited application range in the solution of step length estimation in personal indoor positioning,a step length estimation model based on surface EMG signal and acceleration data is proposed.The surface EMG signal and acceleration data generated by pedestrians during walking is acquired,and the signal is preprocessed by the smooth filtering algorithm.Then,the peak detection algorithm is used to estimate the number of pedestrian steps,and an improved step length estimation method is proposed.The experiment shows that the proposed step length estimation model can realize the step length estimation under different walking speeds.The average error and error rate of the proposed step length estimation are 0.01 m and 1.01%,respectively.And the average error and error rate of the travel distance are 0.78 m and 0.48%,respectively,which meet the requirements of step length estimation for personal indoor positioning and can provide a reference for the application of rehabilitation,market shopping and so on.