Research On Gait Analysis System Of Intelligent Bionic Leg Fusing Bioinformation

Biped Robot with Heterogeneous Legs is a novel robot model, which is an integration of the intelligent prosthesis and biped robot. It, as a highly anthropopathic platform, can be used to study the handicapped’s dynamic characteristics when human being walks with the intelligent prostheses. At the same time, the BRHL can be put into use to research the coordination between the human being and intelligent limb, as well as the walk of heterogeneous legs. These studies will better promote the development of intelligent prosthesis in practice application.In this thesis, the research status of intelligent prosthesis and BRHL is first introduced, and the application development of the Brain-Computer Interface (BCI) in the prosthesis field is expounded. BRHL is an ideal development platform for the research of intelligent bionic legs. And the study of utilizing EEG to control the prosthesis is exploiting a broader perspective in the prosthesis field. The main contents of this thesis include the BRHL gait quantitative analysis and the design of BCI system.In order to use feedback control technology to control BRHL or intelligent prosthesis, it needs to know some typical gait parameters when prosthesis is working. In this thesis, we collected angular velocity and acceleration by MTi inertial sensor to calculate gait parameters quantificationally. In a creative way, the double pendulum and inverted pendulum gait model are put forward to calculate the hip and knee angles, step length combining wavelet transform algorithm. The method applied here is relatively simple and accurate, proved to be an effective way for gait quantitative analysis.Making use of BCI to control prostheses is the process of acquiring control command utilizing EEG, so the point focuses on the design of BCI system. And its basic tasks cover data acquisition and preprocessing, EEG feature extraction and pattern classification. In the thesis, the algorithms of time-domain analysis, frequency-domain analysis, wavelet transform and common spatial pattern are put into use to extract a variety of feature vectors. Then these features are to be classified by Fisher linear discriminant and support vector machines which are based on two different principles. The experimental result shows that the design of BCI is rational and effective and can be used to control the prostheses.