Optimal thigh dip angle reduction by acceleration and angular velocity sensing

Sensors of acceleration and angular velocity are commonly used in gait parameters measurements. One of the applications is calculating the limb segment dip angle. Kalman filter is one of the conventional algorithms to deduce the rotation angle. Two parameters used in Kalman filter are assigned to experiential values. We designed a standard subject experiment and used the ant colony algorithm to find the optimal parameter combination in the two-dimensional space. The experiment result based on a basketball player was perfectly suited for this study and justified the feasibility of the algorithm.