EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix

Kanemoto, Daisuke; Hirose, Tetsuya

doi:https://doi.org/10.1109/ISCAS46773.2023.10181710

EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix

Kanemoto, Daisuke; Hirose, Tetsuya

Proceedings - IEEE International Symposium on Circuits and Systems, 2023, 2023-May, 1-5

アクセス数:45件（2025-03-17 10:04 集計）

固定URL: https://hdl.handle.net/11094/97754

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タイトル	EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix
著者	NRID 1000090603332 1000090603332 researchmap permalink dkanemoto dkanemoto Scopus Author ID 6504308983 6504308983 著者名 Kanemoto, Daisuke
著者	NRID 1000070396315 1000070396315 researchmap permalink hirose_tetsuya hirose_tetsuya Scopus Author ID 9272478400 9272478400 著者名 Hirose, Tetsuya
キーワード等	basis matrix
	BSBL
	compressed sensing
	EEG
内容	Kanemoto D., Hirose T.. EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix. Proceedings - IEEE International Symposium on Circuits and Systems 2023-May, (2023); https://doi.org/10.1109/ISCAS46773.2023.10181710.
抄録	The use of compressed sensing (CS) to achieve low-power consumptions in electroencephalogram (EEG) mea-surement devices has attracted considerable research interest. However, a signal processing issue in utilizing CS is the trade- off between the compression ratio (CR), reconstruction accuracy, and reconstruction time. In this study, we developed a method that resulted in a shortened reconstruction time and a high reconstruction accuracy with a high CR by utilizing selected EEG signals. When EEG signals were sorted using the mean frequency and only the most frequently occurring EEG signals were used in the basis matrix, a compressed EEG signal with an original time length of 1 s could be recovered in only approximately 26 ms, and an average normalized mean square error of 0.11 was achieved at a CR of 5.
会議情報	会議名 2023 IEEE International Symposium on Circuits and Systems (ISCAS) 回次 56 主催機関 IEEE 開催期間 May 21th to May 25th, 2023 開催地 Monterey,Calfornia 開催国アメリカ合衆国
出版者	Institute of Electrical and Electronics Engineers Inc.
収録物名	Proceedings - IEEE International Symposium on Circuits and Systems
巻(号)	2023-May
ページ	1-5
刊行年月	2023-05-21
言語	英語
ハンドルURL	https://hdl.handle.net/11094/97754
PISSN	02714310
関連情報 (isVersionOf)	DOI (出版社版) https://doi.org/10.1109/ISCAS46773.2023.10181710
アクセス権	open access
権利情報	© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
出版タイプ	Accepted Manuscript
カテゴリ	会議発表論文 Conference Paper

資源タイプ	会議発表論文
ローカル資源タイプ	会議発表論文
DCTERMS.bibliographicCitation	Proceedings - IEEE International Symposium on Circuits and Systems. 2023, 2023-May, p. 1-5
DC.title	EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix
DC.creator	Kanemoto, Daisuke
DC.creator	Hirose, Tetsuya
DC.publisher	Institute of Electrical and Electronics Engineers Inc.
DC.language' scheme='DCTERMS.RFC1766	英語
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2023-05-21
DC.identifier	https://doi.org/10.1109/ISCAS46773.2023.10181710
DC.subject	basis matrix
	BSBL
	compressed sensing
	EEG
DC.description	Kanemoto D., Hirose T.. EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix. Proceedings - IEEE International Symposium on Circuits and Systems 2023-May, (2023); https://doi.org/10.1109/ISCAS46773.2023.10181710.
DCTERMS.abstract	The use of compressed sensing (CS) to achieve low-power consumptions in electroencephalogram (EEG) mea-surement devices has attracted considerable research interest. However, a signal processing issue in utilizing CS is the trade- off between the compression ratio (CR), reconstruction accuracy, and reconstruction time. In this study, we developed a method that resulted in a shortened reconstruction time and a high reconstruction accuracy with a high CR by utilizing selected EEG signals. When EEG signals were sorted using the mean frequency and only the most frequently occurring EEG signals were used in the basis matrix, a compressed EEG signal with an original time length of 1 s could be recovered in only approximately 26 ms, and an average normalized mean square error of 0.11 was achieved at a CR of 5.
DC.rights	© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
DC.format	97754
citation_title	EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix
citation_author	Kanemoto, Daisuke
citation_author	Hirose, Tetsuya
citation_publisher	Institute of Electrical and Electronics Engineers Inc.
citation_language	英語
citation_date	2023-05-21
citation_journal_title	Proceedings - IEEE International Symposium on Circuits and Systems
citation_volume	2023-May
citation_firstpage	1
citation_lastpage	5
citation_doi	https://doi.org/10.1109/ISCAS46773.2023.10181710
citation_public_url	https://hdl.handle.net/11094/97754

EEG Measurements with Compressed Sensing Utilizing EEG Signals as the Basis Matrix

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