EEG signal processing techniques and applications—2nd Edition

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dc.contributor.authorWei, Hua-Liang
dc.contributor.authorGuo, Yuzhu
dc.contributor.authorHe, Fei
dc.contributor.authorZhao, Yifan
dc.date.accessioned2025-02-20T09:04:30Z
dc.date.available2025-02-20T09:04:30Z
dc.date.freetoread2025-02-20
dc.date.issued2025-02-01
dc.date.pubOnline2025-01-29
dc.description.abstractElectroencephalography (EEG), as a well-established, non-invasive tool, has been successfully applied to a wide range of conditions due to its many evident advantages, such as economy, portability, easy operation, easy accessibility, and widespread availability in hospitals. EEG signals, with ultra-high time resolution, are vital in understanding brain functions. Traditionally, considerable attention in EEG signal processing and analysis has been paid to understanding brain activities from various perspectives, such as the detection and identification of abnormal frequencies in specific biological states, spatial–temporal and morphological characteristics of neurological disorder behaviours (e.g., paroxysmal or persistent discharges), the response of the brain nervous/neurological system to external stimuli, and the effects and responses to intermittent photic stimulation [1].
dc.description.journalNameSensors
dc.identifier.citationWei H-L, Guo Y, He F, Zhao,Y. (2025) EEG signal processing techniques and applications—2nd Edition. Sensors, Volume 25, Issue 3, February 2025, Article number 805
dc.identifier.eissn1424-8220
dc.identifier.elementsID563515
dc.identifier.issn1424-8220
dc.identifier.issueNo3
dc.identifier.paperNo805
dc.identifier.urihttps://doi.org/10.3390/s25030805
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23483
dc.identifier.volumeNo25
dc.languageEnglish
dc.language.isoen
dc.publisherMDPI
dc.publisher.urihttps://www.mdpi.com/1424-8220/25/3/805
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject4606 Distributed Computing and Systems Software
dc.subject46 Information and Computing Sciences
dc.subjectAnalytical Chemistry
dc.subject3103 Ecology
dc.subject4008 Electrical engineering
dc.subject4009 Electronics, sensors and digital hardware
dc.subject4104 Environmental management
dc.subject4606 Distributed computing and systems software
dc.titleEEG signal processing techniques and applications—2nd Edition
dc.typeArticle
dcterms.dateAccepted2025-01-24

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