Development Of Wearable Gait Measurement System

Gait characteristics refer to the movement characteristic parameters of the lower limbs during human movement,which are mainly related to time and space.The gait status of the lower limbs of the human body is expressed in an objective and quantified manner,which is used to analyze whether the subject has a potential disease or to evaluate the rehabilitation of the lower limbs of the patient.However,the existing gait acquisition system requires a specific environment and space due to its large size,requiring patients to be tested in a hospital,which has the disadvantages of high cost and low efficiency.Therefore,this paper designs a low-cost wearable gait measurement and analysis system,using this device can effectively reduce the cost of collection and simplify the collection work.The main research work is as follows:Inertial sensor(IMU)and pressure sensor signal fusion method are used to extract gait feature information.By using the pressure sensor to extract the pressure data of the tested person’s feet while walking,the relevant gait phase information is calculated after processing;the IMU sensor is used to extract the original data related to the space.After that,the real-time gait phase information and the original data of the spatial information are sampled and stored,and the data stored in the system is packaged and sent to the host computer for final data analysis through wireless communication.This article completes the hardware circuit and programming of sensor signal acquisition,microprocessor peripheral circuit,power management module,FLASH storage module,and wireless communication module.On this basis,through the feature extraction program in the host computer,the raw data of the IMU sensor and the pressure sensor are analyzed and fitted,and the key gait feature parameters are extracted.Aiming at the difficulty of directly converting IMU sensor raw data into gait feature information,this paper designs a method based on raw data processing to extract key attitude angle,pace,step length and other information.First,it is necessary to accurately calibrate the IMU sensor,and use the six-position calibration method to minimize the static error of the IMU sensor;secondly,use the Mahony algorithm to fit the original data of the accelerometer and the gyroscope,and perform closed-loop processing to extract the quaternion.,The quaternion is converted into Euler angles through the conversion formula;finally,the zero velocity detection method is used to process the accumulative integral error of the acceleration to obtain accurate velocity and displacement data.After the system software and hardware design and debugging were completed,the gait test experiment was carried out.The experimental results show that the gait cycle accuracy rate of this system is above 97.5%,the maximum deviation is 100 ms,the step speed accuracy rate is above 90.03%,the maximum measurement deviation is 7cm/s;the step length accuracy rate is 80.05%,the maximum deviation Around 11.7cm.Finally,the feasibility of the system is verified through experiments.