3D Motion Tracking of the Shoulder Joint with Respect to the Thorax Using MARG Sensors and Data Fusion Algorithm

A method for performing 3D motion tracking of the shoulder joint with respect to the thorax, using MARG sensors and a data fusion algorithm, is proposed. Two tests were done: 1) qualitative and quantitative analysis of the response of the sensors, static position and during motion, with and without the proposed data fusion algorithm; 2) motion tracking of the shoulder joint with the upper arm, the thorax, and the shoulder joint respect to the thorax. Qualitative analysis of experimental results showed that despite slight variations regarding the evaluated motion, these variations did not have repercussions on the estimated orientation. Quantitative analysis showed that the estimated orientation did not exhibit significant variations, in five minutes, such as drift errors (about 0.1° in static position and less than 1.8° during motion), variations due to noise or magnetic disturbances (RMSE less than 0.04° static position and less than 1° during motion); no singularity problems were reported. The main contributions of this research are a multisensor data fusion algorithm, which combines the complementary properties of gyroscopes, accelerometers, and magnetometers in order to estimate the 3D orientation of two body segments separately and with respect to another body segment considering the spatial relationship between them; and a method for performing 3D motion tracking of two body segments, based on the estimation of their orientation, including motion compensation. The proposed method is applicable to monitoring devices based on IMU/MARG sensors; the performance was evaluated using a customized motion analysis system.