Research On Gait Analysis Based On MEMS Inertial Sensors

Recent advancement in MEMS,wireless communications and sensor network technology has enabled the development and prevalence of wireless sensor nodes.Wireless sensor nodes that combined data collection,processing and communication into one product have been applied in game interactive,physical training,medical rehabilitation and bipedal biomimetic robots and other fields.And it produced well social and economic effects.The technique of human lower limb gait is based on inertial sensing,which is a branch of the motion capture technique.The device can collect the gait signal by inertial sensor nodes placed in the lower limb.Through the sensor data fusion algorithm,a lot of gait parameters can be calculated,such as phase,displacement.In the reconstruction of the implementation process of walking to the human body movement at the same time,the human gait is analyzed and evaluated.It is of great significance for accurate diagnosis of skeletal muscle,nervous system and abnormal gait diseases.Compared with the current optical system,inertial technology can effectively avoid the interference of factors such as occlusions,illumination and shadow,is a hot topic in recent years.The article in detail on the basis of summarizing existing research content designed an inertial gait analysis system for clinical patients.The system integrated the wireless data acquisition platform based on the inertial sensor,and embedded suitable gait analysis algorithm,so there is some practical value.The study mainly researches three aspects of the gait analysis algorithm,which are the phase estimation,attitude detection and position estimation.The phase estimation uses adaptive peaks method to calculate the step number,and the gait phase points are calculated accordingly;Based on the analysis of characteristics of the data,the foot attitude solution method calibrate sensor error,then set up the error function of quaternion rotation matrix,after real time correcting the attitude data by gradient descent method,the change of the foot attitude is got;The position estimation include position and velocity estimation of the foot in the walking,the research full consider the sensor error and the influence of external noise,the relatively accurate speed information is got by employing the zero velocity update(ZUPT)algorithm,the gait parameters such as the stride length and clearance are got by combination of phase information.Last,the research was tested using normal and abnormal gait to verify the feasibility and applicability of the software platform and algorithm.It turned out that the steps of normal gait was recorded with 100% accuracy,the error of stride length was under 2%;the test result about abnormal gait verified the disease,and fully demonstrated the usefulness of gait analysis system and provide the reference information to related industries.