Compressed Sensing EEG Measurement Technique with Normally Distributed Sampling Series

Okabe, Yuki; Kanemoto, Daisuke; Maida, Osamu et al.

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2022, E105A(10), 1429-1433

Number of Access:574（2025-09-28 05:55 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/97768

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Title
Compressed Sensing EEG Measurement Technique with Normally Distributed Sampling Series
Creator
CreatorName
Okabe, Yuki
NRID
1000090603332 1000090603332
researchmap permalink
dkanemoto dkanemoto
Scopus Author ID
6504308983 6504308983
ORCID
0009-0002-7564-6351 0009-0002-7564-6351
CreatorName
Kanemoto, Daisuke
NRID
1000040346177 1000040346177
researchmap permalink
osamu_maida osamu_maida
Scopus Author ID
6602733779 6602733779
CreatorName
Maida, Osamu
NRID
1000070396315 1000070396315
researchmap permalink
hirose_tetsuya hirose_tetsuya
Scopus Author ID
9272478400 9272478400
ORCID
0000-0003-1997-5097 0000-0003-1997-5097
CreatorName
Hirose, Tetsuya
Subject
compressed sensing
EEG
low-power consumption
normal distribution
random undersampling
Description
Okabe Y., Kanemoto D., Maida O., et al. Compressed Sensing EEG Measurement Technique with Normally Distributed Sampling Series. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E105A, 1429 (2022); https://doi.org/10.1587/transfun.2021EAL2099.
Abstract
We propose a sampling method that incorporates a normally distributed sampling series for EEG measurements using compressed sensing. We confirmed that the ADC sampling count and amount of wirelessly transmitted data can be reduced by 11% while maintaining a reconstruction accuracy similar to that of the conventional method.
Publisher
電子情報通信学会
Institute of Electronics Information Communication Engineers
Source Title
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Volume (Issue)
E105A(10)
Page
1429-1433
Date of Issued
2022-10-01
Language
English
Handle URL
https://hdl.handle.net/11094/97768
PISSN
09168508
eISSN
17451337
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.1587/transfun.2021EAL2099
Access Rights
open access
CopyRight
Copyright © 2022 The Institute of Electronics, Information and Communication Engineers
oaire:version
Version of Record
Category
学術雑誌論文 Journal Article