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Authors: Mera Delimayanti 1 ; Bedy Purnama 2 ; Ngoc Nguyen 3 ; Kunti Mahmudah 3 ; Mamoru Kubo 4 ; Makiko Kakikawa 4 ; Yoichi Yamada 4 and Kenji Satou 4

Affiliations: 1 Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan, Department of Computer and Informatics Engineering, Politeknik Negeri Jakarta, Jakarta, Indonesia ; 2 Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan, Telkom School of Computing, TELKOM University, Bandung, Indonesia ; 3 Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa, Japan ; 4 Institute of Science and Engineering, Kanazawa University, Kanazawa, Japan

ISBN: 978-989-758-353-7

Keyword(s): Breathing Activities, Depth Image, Classification, Support Vector Machine.

Abstract: This paper describes a new approach of the non-contact capturing method of breathing activities using the Kinect depth sensor. To process the data, we utilized feature extraction on time series of mean depth value and optional feature reduction step. The next process implemented a machine learning algorithm to execute clustering on the resulted data. The classification had been realized on four different subjects and then, continued to use 10-fold cross-validation and Support Vector Machine (SVM) classifier. The most efficient classifier is SVM radial with the grid reached the best accuracy for all of the subjects.

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Paper citation in several formats:
Delimayanti, M.; Purnama, B.; Nguyen, N.; Mahmudah, K.; Kubo, M.; Kakikawa, M.; Yamada, Y. and Satou, K. (2019). Clustering and Classification of Breathing Activities by Depth Image from Kinect.In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, ISBN 978-989-758-353-7, pages 264-269. DOI: 10.5220/0007567502640269

@conference{bioinformatics19,
author={Mera Kartika Delimayanti. and Bedy Purnama. and Ngoc Giang Nguyen. and Kunti Robiatul Mahmudah. and Mamoru Kubo. and Makiko Kakikawa. and Yoichi Yamada. and Kenji Satou.},
title={Clustering and Classification of Breathing Activities by Depth Image from Kinect},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,},
year={2019},
pages={264-269},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007567502640269},
isbn={978-989-758-353-7},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS,
TI - Clustering and Classification of Breathing Activities by Depth Image from Kinect
SN - 978-989-758-353-7
AU - Delimayanti, M.
AU - Purnama, B.
AU - Nguyen, N.
AU - Mahmudah, K.
AU - Kubo, M.
AU - Kakikawa, M.
AU - Yamada, Y.
AU - Satou, K.
PY - 2019
SP - 264
EP - 269
DO - 10.5220/0007567502640269

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