Automatic Feature Extraction from Wearable Sensor Data by Use of Machine Learnings
Keita Sato, Masafumi Chida, Yoshihiro Hayakawa, Nahomi Miyamoto Fujiki · 2019
Feasibility of machine leaning techniques for use of automatic detection and analysis of human behavior has been discussed. We focused on the analysis of swing motions in ping-pong play based on the acceleration sensor data of a Smartwatch and to identify slight difference contained in the motion that is unnoticeable by seeing. It has been discussed the feature extraction ability of PCA and auto encoder based on a multilayered neural network combined with clustering methods and shown the possibility of detection of small scale difference in swing motions.