Authors
Hajime Itoh, Naohiko Hanajima, Yohei Muraoka, Makoto Ohata, Masato Mizukami,
Yoshinori Fujihira
Corresponding Author
Hajime Itoh
Available Online 1 June 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.1.5
Keywords
CNN, Gray scale image, Exercises classification, Time-series data.
Abstract
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.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).