Research On Intelligent Perception Technology Of Lower Limb Information Based On Wearable System

The development of wearable systems is very strong in recent years.In order to avoid some security problems,it is necessary for wearable systems to equip identification technology.In addition,wearable systems are also widely used in the collection of human biological information,which will also be further used for health analysis.At present,knee arthritis is a relatively common disease,which is closely related to knee joint injury.And the knee joint injury is related to large moments that occur at the knee joint.Therefore,it is meaningful to monitor the knee joint moment in real time during exercise,so as to give feedback at a proper time point and protect the knee joint.This paper mainly studies the identification and the monitoring of lower limb joint moment based on wearable system.The main research contents include:(1)Design a wearable human biological information collection system.The collected human biological information includes: plantar pressure,inertial data of foot and calf.In addition,the Bluetooth is used to complete the wireless data transmission.(2)The paper mainly uses the characteristics of plantar pressure distribution to identify the human body.Compared with the prior art,the paper simplifies the system and reduces the amount of processed data by reducing the number of pressure sampling points.When establish the characteristic model,10% of the data that deviates from normal range is deleted.In the identification,the data of10?15 gait cycles are used instead of just one for identification.If more than 46% of the gait cycles conforms to the current characteristic model,the result is yes.Eventually,the accuracy of the method reaches more than 98%.(3)Use dynamics and inverse dynamics methods to estimate the moments at the joints of the lower limb.The lower limb of the human body is divided into three segments: foot,calf,and thigh,and the foot and calf are analyzed in turn to estimate the moments at the knee joint.In addition,the method of obtaining static and dynamic parameters of the lower limbs involved in the analysis is explained in detail.(4)Five exercise modes including ordinary walking,backpack walking,turning,ordinary running,and fatigue running are used to verify the feasibility of the moment estimation method described in the paper and the ability of the wearable system to monitor the large moment at the knee joint during exercise.In addition,for the sports that the wearable system is not good at,the paper also gives specific introduction and cases,and finally briefly discusses the method of obtaining the degree of joint wear during the exercise.