A Comparative Analysis of the Motion Recognition Rate by Direction of Push-up Activity Using ELM Algorithm

Sangwoong Kim, Jaeyeong Ryu, Jiwoo Jeong, Dongyeong Kim, Youngho Chai

http://doi.org/10.5626/JOK.2023.50.12.1031

In this paper, we propose a motion recognition system for each direction of push-up activity using ELM algorithm. In the proposed system, a recognized motion consists of three parts. The first part is the process of reading motion data. In the process, the data acquired from the motion capture system is entered into the system"s memory. Then, the system extracts a feature vector from the motion data. The 3D position data converted from the quaternion data value of the motion data is projected onto the X-Y plane, Y-Z plane and Z-X plane of the system, and the values are used as the final feature vector. Feature vectors projected on each plane train different ELM, and a total of three ELM are learned. Finally, by inputting test data to each learned ELM, the final recognition result value is derived. First, before obtaining motion data, as the data set to be trained, general push-ups performed in the correct posture were selected. Second, the upper chest did not go down all the way. Third, only the buttocks came up when bending and lifting. Four, when bending your elbows move away from your upper chest. Finally, mix these motions to build a test dataset.