A machine learning-based method in body movement tracking with a small number of sensors
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https://doi.org/10.54939/1859-1043.j.mst.FEE.2022.171-176Keywords:
Inertial Measurement Unit - IMU; Decision Tree Regression (DTR).Abstract
Most of the current body sensing devices are composed of inertial measurement units (IMUs). The IMU sensors are placed at a different position on the human body and sense their position, rotation, and tilt angle in space, thereby interpolating the movement of parts and the entire human body. Although IMU sensors have high accuracy and fast processing speed, they suffer from a major limitation of being susceptible to external magnetic field sources. This makes the process of re-interpolating the human body become inaccurate in an environment where many strong magnetic fields exist such as metal frames, computers, etc. In this paper, we propose a model to predict the postures of the upper human body, from 03 stable inputs (head, right hand, left hand), thereby reducing the usage of IMU sensors.
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