The Performance of the Depth Camera in Capturing Human Body Motion for Biomechanical Analysis
Abstract: Three-dimensional human movement tracking has long been an important topic in medical and engineering field. Complex camera systems such as Vicon can be used to retrieve very precise motion data. However, the system is more commercial-oriented with a high cost. Besides, it would also be tedious and cumbersome to wear the special markers and suits for tracking. Therefore, there's an urgent need to investigate a cost-effective and markless tool for motion tracking. Microsoft Kinect provides a promising solution with a vast variety of libraries, allowing quick development of 3-D spatial modeling and analysis such as moving skeleton possible. For example, the kinematics of the joints such as acceleration, velocity, and angle changes can be deduced from the spatial position information acquired by the camera. In order to validate whether the Kinect system is sufficient for the analysis in practice, a micro-controller platform Arduino along with Intel® Curie™ IMU (Inertial Measurement Unit) module is developed. In particular, the velocity and Euler angels of joint movements, as well as head orientations are measured and compared between the two systems. In this paper, the goal is to present (i) the use of Kinect Depth sensor for data acquisition, (ii) post-processing with the retrieved data, (iii) validation of the Kinect camera. Results show that the RMS error of the velocity tracking ranges from 1.78% to 23.34%, presenting a good agreement of measurement between the two systems. Moreover, the relative error of the angle tracking is between 4.0% and 24.3%. The results of the head orientations tracking are hard to perform a mathematical analysis due to the noise and invalid data from the camera caused by the loss of tracking. Overall, the accuracy of joint movement tracked by the Kinect camera, particularly velocity, is proved to be acceptable and the depth camera has been found to be an effective tool for kinematic measurement as a cost-effective option. A platform and workflow are now established, thus making future work regarding validation and application possible when the advanced hardware is available.
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