Hand motion capture system based on multiple inertial sensors

Abstract

It is important for many applications to capture hand movements with high accuracy to achieve the natural human-computer interaction, such as games, robotics, rehabilitation, and virtual reality (VR). An ideal hand motion capture solution requires good mobility, unobtrusiveness, and high accuracy. In this demo, we show a hand motion capture system including inertial sensor based data gloves with the square-root cubature Kalman Filter multi-sensor fusion algorithm and a biomechanics sensor-to-segment calibration method. The absolute error of the joint angle is measured. As the result, the proposed system shows good accuracy in both static (RMSE = 1.5°) and dynamic (RMSE = 6.6°) conditions.