Research On Human Gait Analysis Method Based On Plantar Pressure And Foot Posture

Gait is the transformation of the body in the process of walking.It is characterized by symmetry,periodicity,and individual differences.It is an important biological information.In many fields such as rehabilitation medicine,bionic design,and human identification,the research significance and application value of gait have become increasingly prominent.At present,there are two methods for analyzing human gait based on optical image acquisition technology and sensor information perception technology.The latter is more accurate than the former,but it is widely used in the detection of human gait information because of its low cost,ease of integration,and its versatility.This thesis takes the plantar pressure and foot posture in the process of walking as the research object,and uses the corresponding sensors to collect the information of the two.Comprehensive analysis methods such as singular value decomposition,principal component analysis,and fuzzy C-means clustering were used to carry out research on gait recognition based on foot pressure information;using kinematics modeling and analysis methods,The gait model error correction problem based on foot position information was studied.The related research work are as follows.(1)Using the human gait motion simulation software,the correlation between left and right lower limb joint movements was analyzed,the symmetry assumption of the gait movement was verified,and a work curve was performed based on the movements of the knee,knee and hip joints.During the gait cycle,the energy consumption characteristics of the ankle,knee,and hip joints were analyzed.Through the fitting analysis of the knee,knee,and hip flexion angles,the functional relationship of the lower limb joint movement in the periodic gait was obtained.The results of research on the motion characteristics of the lower limbs of the human body have laid a solid foundation for subsequent gait information detection research and development of gait modeling and analysis.(2)In this thesis,the plantar pressure sensor is arranged by point array,and the complementary and redundant relationship between the signals of the array sensor is used to analyze the optimal sensor array configuration scheme for the detection of the foot pressure signal;Acceleration sensors and three-axis gyroscopes constitute an attitude measurement unit for the detection of foot signals;a human gait information collection device is designed and manufactured by integrating the working principle and application characteristics of each sensor.Test results show that the device is reliable and can accurately detect the plantar pressure and foot posture information.(3)Using the singular value decomposition method,the multidimensional foot pressure signal collected by the array sensor is pre-dimensionally reduced to obtain the foot pressure signal with the characteristic separation;the decomposed data is taken as a sample,and the main component analysis method is used to extract the separated signal.The feature information of the gait phase change is used to filter out the redundant and noise information;the fuzzy C-means clustering algorithm is used to define the affiliation characteristics of the standing phase,the single-support phase,and the double-support phase on the time axis in the periodic gait.Based on the video signal as a reference,the frame analysis technology was used to analyze and evaluate the feasibility and accuracy of identifying typical gait based on the plantar pressure signal.In the research process,it effectively overcomes a series of difficulties such as large gait pressure data,high dimensionality and redundancy,weak correlation,and strong noise,and solves the key technical difficulties in human gait recognition.(4)By analyzing the kinematics of the human gait,the error caused by the simplification of the omission of the foot movement in the multi-link model of the lower limb is described.In order to compensate for the model error,the article proposes to model the foot touch motion with the attitude information of the support foot,and calculate the corresponding model correction formula to realize the compensation of the position error of the initial end of the touch-sensitive arm in the original model,thus improving the kinematics solution accuracy.In this thesis,the research results of human gait analysis provide a theoretical basis for the walking drive and stability control of the lower extremity exoskeleton assisted robot,and provide basic compliance for the determination of the sensor placement scheme of the lower limb exoskeleton assisted robot system;gait data collection The methods of preprocessing and feature extraction will form an important part of the key technologies in robots for assisting the exoskeleton of the lower limb.The modification of the gait model will further improve the accuracy of motion control of the lower limb exoskeleton assisted robot.