eprintid: 16097 rev_number: 2 eprint_status: archive userid: 1 dir: disk0/00/01/60/97 datestamp: 2023-12-19 03:22:39 lastmod: 2023-12-19 03:22:39 status_changed: 2023-12-19 03:05:38 type: article metadata_visibility: show creators_name: Abdullah, creators_name: Faye, I. creators_name: Islam, M.R. title: EEG Channel Selection Techniques in Motor Imagery Applications: A Review and New Perspectives ispublished: pub note: cited By 9 abstract: Communication, neuro-prosthetics, and environmental control are just a few applications for disabled persons who use robots and manipulators that use brain-computer interface (BCI) systems. The brain�s motor imagery (MI) signal is an essential input for a brain-related task in BCI applications. Due to their noninvasive, portability, and cost-effectiveness, electroencephalography (EEG) signals are the most widely used input in BCI systems. The EEG data are often collected from more than 100 different locations in the brain; channel selection techniques are critical for selecting the optimum channels for a given application. However, when analyzing EEG data, the principal purpose of channel selection is to reduce computational complexity, improve classification accuracy by avoiding overfitting, and reduce setup time. Several channel selection assessment algorithms, both with and without classification-based methods, extracted appropriate channel subsets using defined criteria. Therefore, based on the exhaustive analysis of the EEG channel selection, this manuscript analyses several existing studies to reduce the number of noisy channels and improve system performance. We review several existing works to find the most promising MI-based EEG channel selection algorithms and associated classification methodologies on various datasets. Moreover, we focus on channel selection methods that choose fewer channels with great precision. Finally, our main finding is that a smaller channel set, typically 10�30 of total channels, provided excellent performance compared to other existing studies. © 2022 by the authors. date: 2022 publisher: MDPI official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144734465&doi=10.3390%2fbioengineering9120726&partnerID=40&md5=8c24d65b5067f864b3bf5d99f13ed89a id_number: 10.3390/bioengineering9120726 full_text_status: none publication: Bioengineering volume: 9 number: 12 refereed: TRUE issn: 23065354 citation: Abdullah and Faye, I. and Islam, M.R. (2022) EEG Channel Selection Techniques in Motor Imagery Applications: A Review and New Perspectives. Bioengineering, 9 (12). ISSN 23065354