Literature DB >> 30414824

Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects.

Camille Jeunet1, Bertrand Glize2, Aileen McGonigal3, Jean-Marie Batail4, Jean-Arthur Micoulaud-Franchi5.   

Abstract

Many Brain Computer Interface (BCI) and neurofeedback studies have investigated the impact of sensorimotor rhythm (SMR) self-regulation training procedures on motor skills enhancement in healthy subjects and patients with motor disabilities. This critical review aims first to introduce the different definitions of SMR EEG target in BCI/Neurofeedback studies and to summarize the background from neurophysiological and neuroplasticity studies that led to SMR being considered as reliable and valid EEG targets to improve motor skills through BCI/neurofeedback procedures. The second objective of this review is to introduce the main findings regarding SMR BCI/neurofeedback in healthy subjects. Third, the main findings regarding BCI/neurofeedback efficiency in patients with hypokinetic activities (in particular, motor deficit following stroke) as well as in patients with hyperkinetic activities (in particular, Attention Deficit Hyperactivity Disorder, ADHD) will be introduced. Due to a range of limitations, a clear association between SMR BCI/neurofeedback training and enhanced motor skills has yet to be established. However, SMR BCI/neurofeedback appears promising, and highlights many important challenges for clinical neurophysiology with regards to therapeutic approaches using BCI/neurofeedback.
Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  ADHD; Brain Computer Interface; Closed loop; Motor ability; Neurofeedback; Stroke

Mesh:

Year:  2018        PMID: 30414824     DOI: 10.1016/j.neucli.2018.10.068

Source DB:  PubMed          Journal:  Neurophysiol Clin        ISSN: 0987-7053            Impact factor:   3.734


  14 in total

1.  Quantitative Analysis of EEG Power Spectrum and EMG Median Power Frequency Changes after Continuous Passive Motion Mirror Therapy System.

Authors:  Taewoong Park; Mina Lee; Taejong Jeong; Yong-Il Shin; Sung-Min Park
Journal:  Sensors (Basel)       Date:  2020-04-21       Impact factor: 3.576

2.  Optimization of Surface Electromyography-Based Neurofeedback Rehabilitation Intervention System.

Authors:  Wenlin Sun; Yujun Qi; Yang Sun; Tiantian Zhao; Xiaoyong Su; Yang Liu
Journal:  J Healthc Eng       Date:  2021-03-17       Impact factor: 2.682

Review 3.  Discussion on the Rehabilitation of Stroke Hemiplegia Based on Interdisciplinary Combination of Medicine and Engineering.

Authors:  Xiaowei Sun; Ke Xu; Yuqing Shi; Hongtao Li; Ruobing Li; Siyu Yang; Hong Jin; Chuwen Feng; Baitao Li; Chunyue Xing; Yuanyuan Qu; Qingyong Wang; Yinghua Chen; Tiansong Yang
Journal:  Evid Based Complement Alternat Med       Date:  2021-03-17       Impact factor: 2.629

4.  Functional Reorganization After Four-Week Brain-Computer Interface-Controlled Supernumerary Robotic Finger Training: A Pilot Study of Longitudinal Resting-State fMRI.

Authors:  Yuan Liu; Shuaifei Huang; Zhuang Wang; Fengrui Ji; Dong Ming
Journal:  Front Neurosci       Date:  2022-02-11       Impact factor: 4.677

5.  Sensorimotor Rhythm-Brain Computer Interface With Audio-Cue, Motor Observation and Multisensory Feedback for Upper-Limb Stroke Rehabilitation: A Controlled Study.

Authors:  Xin Li; Lu Wang; Si Miao; Zan Yue; Zhiming Tang; Liujie Su; Yadan Zheng; Xiangzhen Wu; Shan Wang; Jing Wang; Zulin Dou
Journal:  Front Neurosci       Date:  2022-03-11       Impact factor: 4.677

6.  A flexible and accurate method for electroencephalography rhythms extraction based on circulant singular spectrum analysis.

Authors:  Hai Hu; Zihang Pu; Peng Wang
Journal:  PeerJ       Date:  2022-03-23       Impact factor: 2.984

7.  Individual Sensory Modality Dominance as an Influential Factor in the Prefrontal Neurofeedback Training for Spatial Processing: A Functional Near-Infrared Spectroscopy Study.

Authors:  Takeshi Sakurada; Mayuko Matsumoto; Shin-Ichiroh Yamamoto
Journal:  Front Syst Neurosci       Date:  2022-02-10

8.  Effects of unilateral dynamic handgrip on reaction time and error rate.

Authors:  Arash Mirifar; Mengkai Luan; Felix Ehrlenspiel
Journal:  Cogn Process       Date:  2022-02-10

9.  Neurofeedback-Linked Suppression of Cortical β Bursts Speeds Up Movement Initiation in Healthy Motor Control: A Double-Blind Sham-Controlled Study.

Authors:  Shenghong He; Claudia Everest-Phillips; Andrew Clouter; Peter Brown; Huiling Tan
Journal:  J Neurosci       Date:  2020-04-13       Impact factor: 6.167

10.  Success of Hand Movement Imagination Depends on Personality Traits, Brain Asymmetry, and Degree of Handedness.

Authors:  Elena V Bobrova; Varvara V Reshetnikova; Elena A Vershinina; Alexander A Grishin; Pavel D Bobrov; Alexander A Frolov; Yury P Gerasimenko
Journal:  Brain Sci       Date:  2021-06-25
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