Study of gait symmetry quantification and its application to intelligent prosthetic leg development

Human bipedal walking is symmetrical, stable and efficiency optimal. To clarify the essential relationship in human gait, accelerometers and rate gyroscopes are mounted on waist and lower extremities of subject to acquire kinematics information during walking. By employing Principal Component Analysis (PCA), kinematics signals of one side are reconstructed using that of opposite side. The reconstructed signals match the acquired ones very well, which verifies the existence of strong linear correlations in healthy human gait. To evaluate the symmetry of gait quantitatively, several classical temporal-spatial features for gait calculated by algorithms involving autocorrelation function are selected for construction of quantitative criterions by combining with symmetry indices. For the validation of gait symmetry quantification scheme, level walking experiments including healthy human subjects and human-intelligent prosthetic leg coupling system are conducted. Results indicate the correctness and effectiveness of the proposed scheme and gait symmetry analysis shows great potential in the field of bio-medical rehabilitation.