Motion Trajectory Analysis Based on MARG Sensors for Wearable Computing

The MARG (Magnetic, Angular Rate, and Gravity) sensor system, which consists of a MEMS tri-axis accelerometer, a MEMS tri-axis gyroscope and a MEMS tri-axis magnetometer, has a wide application prospect in the wearable computing field. But due to the difficulty of removing gravity and the error cumulating, the MARG sensors have not been applied to the motion trajectory analysis and computing. This paper presents a method for trajectory analysis and computing with the Finite Automation tool using MARG sensors. The information needed to adjust the acceleration signal is offered when the state of the motion is recognized by Finite Automation. The method is used on the base of gravity removing process, which is implemented by the orientation estimation using gradient descent algorithm. This method can accurately implement the segmentation and analysis of a complex motion and get the trajectory of the motion, which helps us recognize and comprehend the meaning of the motion. In this paper, the method is applied to the arm motion trajectory analysis and computing, experiment result shows the efficiency of the method.