A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application

Patients with severe CNS injuries struggle primarily with their sensorimotor function and communication with the outside world. There is an urgent need for advanced neural rehabilitation and intelligent interaction technology to provide help for patients with nerve injuries. Recent studies have esta...

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Autores principales: Orban, Mostafa, Elsamanty, Mahmoud, Guo, Kai, Zhang, Senhao, Yang, Hongbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9774292/
https://www.ncbi.nlm.nih.gov/pubmed/36550974
http://dx.doi.org/10.3390/bioengineering9120768
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author Orban, Mostafa
Elsamanty, Mahmoud
Guo, Kai
Zhang, Senhao
Yang, Hongbo
author_facet Orban, Mostafa
Elsamanty, Mahmoud
Guo, Kai
Zhang, Senhao
Yang, Hongbo
author_sort Orban, Mostafa
collection PubMed
description Patients with severe CNS injuries struggle primarily with their sensorimotor function and communication with the outside world. There is an urgent need for advanced neural rehabilitation and intelligent interaction technology to provide help for patients with nerve injuries. Recent studies have established the brain-computer interface (BCI) in order to provide patients with appropriate interaction methods or more intelligent rehabilitation training. This paper reviews the most recent research on brain-computer-interface-based non-invasive rehabilitation systems. Various endogenous and exogenous methods, advantages, limitations, and challenges are discussed and proposed. In addition, the paper discusses the communication between the various brain-computer interface modes used between severely paralyzed and locked patients and the surrounding environment, particularly the brain-computer interaction system utilizing exogenous (induced) EEG signals (such as P300 and SSVEP). This discussion reveals with an examination of the interface for collecting EEG signals, EEG components, and signal postprocessing. Furthermore, the paper describes the development of natural interaction strategies, with a focus on signal acquisition, data processing, pattern recognition algorithms, and control techniques.
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spelling pubmed-97742922022-12-23 A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application Orban, Mostafa Elsamanty, Mahmoud Guo, Kai Zhang, Senhao Yang, Hongbo Bioengineering (Basel) Review Patients with severe CNS injuries struggle primarily with their sensorimotor function and communication with the outside world. There is an urgent need for advanced neural rehabilitation and intelligent interaction technology to provide help for patients with nerve injuries. Recent studies have established the brain-computer interface (BCI) in order to provide patients with appropriate interaction methods or more intelligent rehabilitation training. This paper reviews the most recent research on brain-computer-interface-based non-invasive rehabilitation systems. Various endogenous and exogenous methods, advantages, limitations, and challenges are discussed and proposed. In addition, the paper discusses the communication between the various brain-computer interface modes used between severely paralyzed and locked patients and the surrounding environment, particularly the brain-computer interaction system utilizing exogenous (induced) EEG signals (such as P300 and SSVEP). This discussion reveals with an examination of the interface for collecting EEG signals, EEG components, and signal postprocessing. Furthermore, the paper describes the development of natural interaction strategies, with a focus on signal acquisition, data processing, pattern recognition algorithms, and control techniques. MDPI 2022-12-05 /pmc/articles/PMC9774292/ /pubmed/36550974 http://dx.doi.org/10.3390/bioengineering9120768 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Orban, Mostafa
Elsamanty, Mahmoud
Guo, Kai
Zhang, Senhao
Yang, Hongbo
A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application
title A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application
title_full A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application
title_fullStr A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application
title_full_unstemmed A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application
title_short A Review of Brain Activity and EEG-Based Brain–Computer Interfaces for Rehabilitation Application
title_sort review of brain activity and eeg-based brain–computer interfaces for rehabilitation application
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9774292/
https://www.ncbi.nlm.nih.gov/pubmed/36550974
http://dx.doi.org/10.3390/bioengineering9120768
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