Wearable Health Monitoring System Based On Walking Locomotion

In recent years,the Human Health Monitoring Systems(HMS)have attracted a lot of attention.People can have regular physical examinations through various sophisticated testing instruments in hospitals to know their health status,but it is difficult to get to the specific environment and use the special equipment at any time in daily life.Wearable health monitoring system can realize human health monitoring without relying on fixed medical places and complex instruments and equipment,which has great research value and application value.This paper studies a wearable health monitoring system based on walking locomotion,which uses the built-in sensors in smart phones to monitor human health basing on walking locomotion.The main research contents are as follows:(1)The characteristics of lower limb periodic changes during pedestrian walking were studied.Key gait event were extracted for gait cycle segmentation,and a pedestrian stepping detection algorithm based on thigh angle change is implemented A simplified step length model is proposed to realize the calculation of pedestrian step length.(2)In this paper,the algorithm of pedestrian dead reckoning is studied,and the heading drift is suppressed by the flexible fusion of magnetometer data,so as to avoid the filtering divergence caused by the interference of indoor environmental magnetic field.Combined with the monitoring of pedestrian activity floor based on the barometer,the indoor three-dimensional pedestrian activity tracking is implemented,and the phenomenon of pedestrian track crossing the wall is corrected through the map matching based on particle filter,so as to optimize the estimated pedestrian track.(3)The differences of pedestrian gait parameters between different age groups and the same age groups were studied and the correlation between basic physical information of pedestrians and gait parameters was analyzed.It is concluded that the parameters such as stride length,stride speed,stride frequency and peak of thigh swing angle are closely related to the motor function of human lower limbs.In order to verify the pedestrian indoor tracking algorithm,walking experiments were carried out along three paths with different degrees of complexity.The relative return errors of the three walking tracks were 0.37%,0.38% and 1.22% respectively,indicating that this algorithm has high precision and can realize the monitoring of pedestrian track.In the health monitoring experiment,36 subjects were tested.The results showed that the gait parameters of the subjects were significantly different in different ages.In the same age group,gait parameters of people with poor physical fitness were significantly different from those of others,indicating the accuracy and effectiveness of pedestrian health monitoring through walking locomotion.