Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring

Sanhe Duan; Qi Guo; Siyuan Lv; Ying Liu; Hong Tang; Dan Liu; Jinwei Sun; Qisong Wang

doi:10.1007/978-3-031-51455-5_43

Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring

Sanhe Duan^*
, Qi Guo
, Siyuan Lv
, Ying Liu
, Hong Tang
, Dan Liu
, Jinwei Sun
, Qisong Wang

^*Corresponding author for this work

Harbin Institute of Technology
Heilongjiang Provincial Hospital

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Depth of anesthesia monitoring has been adopted in clinic in the recent years. However, misjudgments could occur under certain circumstances, which would harm patients mentally or even physically. In this article, we have proposed a novel hybrid EEG-fNIRS signal acquisition system with self-designed EEG and fNIRS acquisition modules. Results show that the EEG module has an indication error between 4 and 14%, the fNIRS module could drive laser sources and acquire signals with a 0.005 V converted signal resolution, and the system could acquire, visualize and save the data with a stable running time of about 1 h. The proposed system has huge potential for DoA monitoring.

Original language	English
Title of host publication	12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1
Subtitle of host publication	Biomedical Signal Processing, Imaging and Rehabilitation Engineering
Editors	Guangzhi Wang, Dezhong Yao, Zhongze Gu, Yi Peng, Shanbao Tong, Chengyu Liu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	388-397
Number of pages	10
ISBN (Print)	9783031514548
DOIs	https://doi.org/10.1007/978-3-031-51455-5_43
State	Published - 2024
Externally published	Yes
Event	12th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2023 - Suzhou, China Duration: 18 May 2023 → 21 May 2023

Publication series

Name	IFMBE Proceedings
Volume	103
ISSN (Print)	1680-0737
ISSN (Electronic)	1433-9277

Conference

Conference	12th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2023
Country/Territory	China
City	Suzhou
Period	18/05/23 → 21/05/23

Keywords

Depth of anesthesia monitoring
EEG
Hybrid-sourced data
fNIRS

Access to Document

10.1007/978-3-031-51455-5_43

Cite this

Duan, S., Guo, Q., Lv, S., Liu, Y., Tang, H., Liu, D., Sun, J., & Wang, Q. (2024). Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring. In G. Wang, D. Yao, Z. Gu, Y. Peng, S. Tong, & C. Liu (Eds.), 12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1: Biomedical Signal Processing, Imaging and Rehabilitation Engineering (pp. 388-397). (IFMBE Proceedings; Vol. 103). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-51455-5_43

Duan, Sanhe ; Guo, Qi ; Lv, Siyuan et al. / Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring. 12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1: Biomedical Signal Processing, Imaging and Rehabilitation Engineering. editor / Guangzhi Wang ; Dezhong Yao ; Zhongze Gu ; Yi Peng ; Shanbao Tong ; Chengyu Liu. Springer Science and Business Media Deutschland GmbH, 2024. pp. 388-397 (IFMBE Proceedings).

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title = "Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring",

abstract = "Depth of anesthesia monitoring has been adopted in clinic in the recent years. However, misjudgments could occur under certain circumstances, which would harm patients mentally or even physically. In this article, we have proposed a novel hybrid EEG-fNIRS signal acquisition system with self-designed EEG and fNIRS acquisition modules. Results show that the EEG module has an indication error between 4 and 14\%, the fNIRS module could drive laser sources and acquire signals with a 0.005 V converted signal resolution, and the system could acquire, visualize and save the data with a stable running time of about 1 h. The proposed system has huge potential for DoA monitoring.",

keywords = "Depth of anesthesia monitoring, EEG, Hybrid-sourced data, fNIRS",

author = "Sanhe Duan and Qi Guo and Siyuan Lv and Ying Liu and Hong Tang and Dan Liu and Jinwei Sun and Qisong Wang",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 12th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2023 ; Conference date: 18-05-2023 Through 21-05-2023",

year = "2024",

doi = "10.1007/978-3-031-51455-5\_43",

language = "英语",

isbn = "9783031514548",

series = "IFMBE Proceedings",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "388--397",

editor = "Guangzhi Wang and Dezhong Yao and Zhongze Gu and Yi Peng and Shanbao Tong and Chengyu Liu",

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Duan, S, Guo, Q, Lv, S, Liu, Y, Tang, H, Liu, D, Sun, J & Wang, Q 2024, Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring. in G Wang, D Yao, Z Gu, Y Peng, S Tong & C Liu (eds), 12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1: Biomedical Signal Processing, Imaging and Rehabilitation Engineering. IFMBE Proceedings, vol. 103, Springer Science and Business Media Deutschland GmbH, pp. 388-397, 12th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2023, Suzhou, China, 18/05/23. https://doi.org/10.1007/978-3-031-51455-5_43

Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring. / Duan, Sanhe; Guo, Qi; Lv, Siyuan et al.
12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1: Biomedical Signal Processing, Imaging and Rehabilitation Engineering. ed. / Guangzhi Wang; Dezhong Yao; Zhongze Gu; Yi Peng; Shanbao Tong; Chengyu Liu. Springer Science and Business Media Deutschland GmbH, 2024. p. 388-397 (IFMBE Proceedings; Vol. 103).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring

AU - Duan, Sanhe

AU - Guo, Qi

AU - Lv, Siyuan

AU - Liu, Ying

AU - Tang, Hong

AU - Liu, Dan

AU - Sun, Jinwei

AU - Wang, Qisong

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - Depth of anesthesia monitoring has been adopted in clinic in the recent years. However, misjudgments could occur under certain circumstances, which would harm patients mentally or even physically. In this article, we have proposed a novel hybrid EEG-fNIRS signal acquisition system with self-designed EEG and fNIRS acquisition modules. Results show that the EEG module has an indication error between 4 and 14%, the fNIRS module could drive laser sources and acquire signals with a 0.005 V converted signal resolution, and the system could acquire, visualize and save the data with a stable running time of about 1 h. The proposed system has huge potential for DoA monitoring.

AB - Depth of anesthesia monitoring has been adopted in clinic in the recent years. However, misjudgments could occur under certain circumstances, which would harm patients mentally or even physically. In this article, we have proposed a novel hybrid EEG-fNIRS signal acquisition system with self-designed EEG and fNIRS acquisition modules. Results show that the EEG module has an indication error between 4 and 14%, the fNIRS module could drive laser sources and acquire signals with a 0.005 V converted signal resolution, and the system could acquire, visualize and save the data with a stable running time of about 1 h. The proposed system has huge potential for DoA monitoring.

KW - Depth of anesthesia monitoring

KW - EEG

KW - Hybrid-sourced data

KW - fNIRS

UR - https://www.scopus.com/pages/publications/85192167336

U2 - 10.1007/978-3-031-51455-5_43

DO - 10.1007/978-3-031-51455-5_43

M3 - 会议稿件

AN - SCOPUS:85192167336

SN - 9783031514548

T3 - IFMBE Proceedings

SP - 388

EP - 397

BT - 12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1

A2 - Wang, Guangzhi

A2 - Yao, Dezhong

A2 - Gu, Zhongze

A2 - Peng, Yi

A2 - Tong, Shanbao

A2 - Liu, Chengyu

PB - Springer Science and Business Media Deutschland GmbH

T2 - 12th Asian-Pacific Conference on Medical and Biological Engineering, APCMBE 2023

Y2 - 18 May 2023 through 21 May 2023

ER -

Duan S, Guo Q, Lv S, Liu Y, Tang H, Liu D et al. Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring. In Wang G, Yao D, Gu Z, Peng Y, Tong S, Liu C, editors, 12th Asian-Pacific Conference on Medical and Biological Engineering - Proceedings of APCMBE 2023, Volume 1: Biomedical Signal Processing, Imaging and Rehabilitation Engineering. Springer Science and Business Media Deutschland GmbH. 2024. p. 388-397. (IFMBE Proceedings). doi: 10.1007/978-3-031-51455-5_43

Wireless EEG-fNIRS Fusion Signal Acquisition System for Depth of Anesthesia Monitoring

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