Comparison of Filtering Methods in Measuring Human ZMP Using Kinect Sensor

This paper aims to verify the detection accuracy of Zero Moment Point (ZMP) measurements of the human body using the Kinect sensor. In this paper, ZMP is measured based on a multi-link model of the human body. ZMP calculation algorithms using a Low Pass Filter (LPF) and Savitzky-Golay (SG) filter were constructed to investigate filtering methods that can measure ZMP with high accuracy and small lag. The accuracy and responsiveness of these filters were evaluated through experiments measuring ZMP during human walking. Experimental results show that the detection error in ZMP is dominated by the differential noise in the acceleration calculation, and applying the filter only to measured acceleration values increases responsiveness with the same accuracy as when applied to ZMP. We also found that the SG filter is superior to LPF in noise suppression and responsiveness of ZMP measurements, though it occurs overshoot in measurements.