A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface
dc.citation.issue | 6 | |
dc.citation.volume | 21 | |
dc.contributor.author | Singh A | |
dc.contributor.author | Hussain AA | |
dc.contributor.author | Lal S | |
dc.contributor.author | Guesgen HW | |
dc.contributor.editor | Tran Y | |
dc.coverage.spatial | Switzerland | |
dc.date.accessioned | 2023-11-14T02:19:28Z | |
dc.date.accessioned | 2023-11-20T01:38:09Z | |
dc.date.available | 2021-03-20 | |
dc.date.available | 2023-11-14T02:19:28Z | |
dc.date.available | 2023-11-20T01:38:09Z | |
dc.date.issued | 2021-03-20 | |
dc.description.abstract | Motor imagery (MI) based brain-computer interface (BCI) aims to provide a means of communication through the utilization of neural activity generated due to kinesthetic imagination of limbs. Every year, a significant number of publications that are related to new improvements, challenges, and breakthrough in MI-BCI are made. This paper provides a comprehensive review of the electroencephalogram (EEG) based MI-BCI system. It describes the current state of the art in different stages of the MI-BCI (data acquisition, MI training, preprocessing, feature extraction, channel and feature selection, and classification) pipeline. Although MI-BCI research has been going for many years, this technology is mostly confined to controlled lab environments. We discuss recent developments and critical algorithmic issues in MI-based BCI for commercial deployment. | |
dc.description.confidential | false | |
dc.edition.edition | March 2021 | |
dc.format.pagination | 1-35 | |
dc.identifier.author-url | https://www.ncbi.nlm.nih.gov/pubmed/33804611 | |
dc.identifier.citation | Singh A, Hussain AA, Lal S, Guesgen HW. (2021). A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface.. Sensors (Basel). 21. 6. (pp. 1-35). | |
dc.identifier.doi | 10.3390/s21062173 | |
dc.identifier.eissn | 1424-8220 | |
dc.identifier.elements-type | journal-article | |
dc.identifier.issn | 1424-8220 | |
dc.identifier.number | ARTN 2173 | |
dc.identifier.pii | s21062173 | |
dc.identifier.uri | https://mro.massey.ac.nz/handle/10179/69161 | |
dc.language | eng | |
dc.publisher | MDPI (Basel, Switzerland) | |
dc.publisher.uri | https://www.mdpi.com/1424-8220/21/6/2173 | |
dc.relation.isPartOf | Sensors (Basel) | |
dc.rights | (c) 2021 The Author/s | |
dc.rights | CC BY | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | BCI calibration | |
dc.subject | BCI illiteracy | |
dc.subject | BCI training | |
dc.subject | adaptive BCI | |
dc.subject | asynchronous BCI | |
dc.subject | brain–computer interface (BCI) | |
dc.subject | electroencephalography (EEG) | |
dc.subject | motor imagery | |
dc.subject | online BCI | |
dc.subject | Brain-Computer Interfaces | |
dc.subject | Electroencephalography | |
dc.subject | Imagination | |
dc.title | A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface | |
dc.type | Journal article | |
pubs.elements-id | 441942 | |
pubs.organisational-group | Other |
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