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...
Autores principales: | , , , , |
---|---|
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 |
_version_ | 1784855371999870976 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9774292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT orbanmostafa areviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT elsamantymahmoud areviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT guokai areviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT zhangsenhao areviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT yanghongbo areviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT orbanmostafa reviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT elsamantymahmoud reviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT guokai reviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT zhangsenhao reviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication AT yanghongbo reviewofbrainactivityandeegbasedbraincomputerinterfacesforrehabilitationapplication |