Development of a wireless sensor network for the measurement of human joint angles
The development of a wireless sensor network (WSN) that measures joint angles of the human body is reported. Its principle of operation is based on measuring the alignment of the different segments of the limb being tracked with the earth's gravity and magnetic fields. The focus is on measurements at the shoulder and elbow joints. These are tracked with 3 and 2 degrees of freedom respectively. In order to validate the accuracy of the proposed WSN, experiments are performed with arm movements on each degree of freedom and the WSN's measurements are compared with those of a professional motion capture (mocap) system that uses infra-red (IR) cameras and markers. The average root mean square error (RMSE) across all degrees of freedom was found to be 1.39° and 2.18° when tested on a spherical coordinate system and human arm respectively. Finally, the causes for this increase on the RMSE are discussed in terms of the effects of the arm's skin and muscles on the alignment of the sensors. It is found that when the user performs the greatest efforts to make the movements, the WSN deviates the most from the IR mocap system. In the degree of freedom that is most affected, the RMSE increases from 0.96° to 2.62°. This is an increase of 173%.
Dai Meng and Gustavo Vejarano, "Development of a Wireless Sensor Network for the Measurement of Human Joint Angles," in IEEE International Conference on Connected Vehicles and Expo (ICCVE'13), Las Vegas, NV, USA, Dec. 2013. URL: https://doi.org/10.1109/ICCVE.2013.6799820
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