Exercise classification using CNN with image frames produced from time-series motion data

Exercise support systems for the elderly have been developed and some were equipped with a motion sensor to evaluate their exercise motion. Normally, it provides three-dimensional time-series data of over 20 joints. In this study, we propose to apply Convolutional Neural Network (CNN) methodology to the motion evaluation. The method converts the motion data of one exercise interval into one gray scale image. From simulation results, the CNN was possible to classify the images into specified motions.