Time-independent human gait modeling using accelerometry data

Human gait analysis has been widely used in many fields of work. Numerous sensor types are applied in gait analysis. Accelerometer is a sensor that is famous to use. Gait was previously analyzed based on time-dependent data from an accelerometer. This will face some problems when a test subject is walking at different speeds. To correct such problem, a time-independent mathematical model for human gait is proposed. A three-axis accelerometer is installed at each foot to collect all three-axis data in Cartesian coordinate. These data are subsequently transformed to spherical coordinate to form a 3-D gait trajectory. Polynomial surface fitting technique is applied to the measured trajectory. In the experimental, about 194 gait cycles are tested and compare with simulation data. From the experimental results, accuracy of the proposed gait model is more than 85%.