Research On Key Techniques Of Human Gait Analysis Based On MEMS Inertial Sensor

Gait analysis is to transform the information into a digital abstract model by detecting the posture and position of the human body,which is to express the posture of the target and the information reflected by the posture at different moments.With the improvement of modern medical technology and the development of nursing science,the rehabilitation of patients is gradually moving towards quantitative and scientific development.The application of gait analysis technology in the rehabilitation process of lower limbs can effectively monitor the rehabilitation status of patients' lower limbs and provide quantitative basis for the formulation of rehabilitation plan.In this paper,the gait analysis technology based on MEMS(Micro Electro Mechanical Systems,MEMS)inertial sensor was studied.By studying motion parameter acquisition,multiple MEMS inertial sensor data fusion processing,a composite profile fitting method based on finite state machine,etc,the accuracy of gait cycle division and gait parameter calculation has been improved.The research contents of this paper mainly include the following aspects:(1)MEMS inertial sensor unit was mainly composed of accelerometer,gyroscope and magnetometer.In order to make the obtained acceleration value,angular velocity value and magnetometer value accurately to reflect the motion state of the lower limb structure,different data fusion algorithms and ellipsoid fitting calibration algorithm of magnetometer were studied.(2)Based on the human body model and the human body movement theory,the motion state model of lower limbs was studied to determine the key parts that could accurately express the characteristics of gait and the sources of measurement errors and the treatment methods were analyzed.MEMS inertial sensor units were installed in each key part of the lower limb respectively and the corresponding state parameters were collected under different motion states.In this paper,the adaptive algorithm of state machine was innovatively proposed to solve the problem of attitude fitting of transient switching of different gait under different motion state characteristics,which greatly improved the real-time performance and test accuracy of the test system.The effectiveness and feasibility of the multi-attitude fitting method and the realtime switching algorithm were verified by experiments.(3)On the basis of obtaining the motion state parameters of the lower limbs,the algorithm of dividing the gait cycle and the calculation methods of gait parameters such as gait frequency,step deviation Angle and stride length are further studied.After the zero-rate update algorithm and the gait cycle division algorithm were studied,the gait parameter test system based on the algorithm was compared with the HTC(High Technology Computer Corporation,HTC)optical system.