@inproceedings{c8c47e5fb49e43de9e7c43b28756124c,
title = "Pondushand: Measure user{\textquoteright}s weight feeling by photo sensor array around forearm",
abstract = "Weight feeling is important for musical instrument training and physical workout training. But it is difficult to convey accurate information about weight feeling to trainer with visual or verbal information.This study measures weight feeling on muscles when playing a piano keyboard or doing push-ups using a wearable device. To do that, the muscle deformation data is measured by a photo-sensor array wrapped around the forearm. This data is input to a trained Support Vector Regression (SVR) classifier that estimates weight feeling as output. As a result of our experiment, the correlation coefficient between the measured value and the estimated value was 0.911 while RMSE and MAE were 236 g and150 g respectively when estimating weights up to 2000 g. In future work, we want to use this technique under many arm posture.",
keywords = "Muscle, Photosensor, Weight feeling",
author = "Hosono Satoshi and Shoji Nishimura and Ken Iwasaki and Emi Tamaki",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s).; SIGGRAPH Asia 2019 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2019 ; Conference date: 17-11-2019 Through 20-11-2019",
year = "2019",
month = nov,
day = "17",
doi = "10.1145/3355056.3364552",
language = "English",
series = "SIGGRAPH Asia 2019 Posters, SA 2019",
publisher = "Association for Computing Machinery, Inc",
booktitle = "SIGGRAPH Asia 2019 Posters, SA 2019",
}