Literature DB >> 31380763

EMG- Versus EEG-Triggered Electrical Stimulation for Inducing Corticospinal Plasticity.

Mads Jochumsen, Muhammad S Navid, Usman Rashid, Heidi Haavik, Imran K Niazi.   

Abstract

Brain-computer interfaces have been proposed for stroke rehabilitation. Motor cortical activity derived from the electroencephalography (EEG) can trigger external devices that provide congruent sensory feedback. However, many stroke patients regain residual muscle (EMG: electromyography) control due to spontaneous recovery and rehabilitation; therefore, EEG may not be necessary as a control signal. In this paper, a direct comparison was made between the induction of corticospinal plasticity using either EEG- or EMG-controlled electrical nerve stimulation. Twenty healthy participants participated in two intervention sessions consisting of EEG- and EMG-controlled electrical stimulation. The sessions consisted of 50 pairings between foot dorsiflexion movements (decoded through either EEG or EMG) and electrical stimulation of the common peroneal nerve. Before, immediately after and 30 minutes after the intervention, 15 motor evoked potentials (MEPs) were elicited in tibialis anterior through transcranial magnetic stimulation. Increased MEPs were observed immediately after (62 ± 26%, 73 ± 27% for EEG- and EMG-triggered electrical stimulation, respectively) and 30 minutes after each of the two interventions (79 ± 26% and 72 ± 27%) compared to the pre-intervention measurement. There was no difference between the interventions. Both EEG- and EMG-controlled electrical stimulation can induce corticospinal plasticity which suggests that stroke patients with residual EMG can use that modality instead of EEG to trigger stimulation.

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Year:  2019        PMID: 31380763     DOI: 10.1109/TNSRE.2019.2932104

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  4 in total

1.  Associative cued asynchronous BCI induces cortical plasticity in stroke patients.

Authors:  Muhammad Samran Navid; Usman Rashid; Imran Khan Niazi; Imran Amjad; Sharon Olsen; Heidi Haavik; Gemma Alder; Nitika Kumari; Nada Signal; Denise Taylor; Dario Farina; Mads Jochumsen
Journal:  Ann Clin Transl Neurol       Date:  2022-04-30       Impact factor: 5.430

2.  EEG Headset Evaluation for Detection of Single-Trial Movement Intention for Brain-Computer Interfaces.

Authors:  Mads Jochumsen; Hendrik Knoche; Troels Wesenberg Kjaer; Birthe Dinesen; Preben Kidmose
Journal:  Sensors (Basel)       Date:  2020-05-14       Impact factor: 3.576

3.  Decoding Attempted Hand Movements in Stroke Patients Using Surface Electromyography.

Authors:  Mads Jochumsen; Imran Khan Niazi; Muhammad Zia Ur Rehman; Imran Amjad; Muhammad Shafique; Syed Omer Gilani; Asim Waris
Journal:  Sensors (Basel)       Date:  2020-11-26       Impact factor: 3.576

4.  An EEG-based asynchronous MI-BCI system to reduce false positives with a small number of channels for neurorehabilitation: A pilot study.

Authors:  Minsu Song; Hojun Jeong; Jongbum Kim; Sung-Ho Jang; Jonghyun Kim
Journal:  Front Neurorobot       Date:  2022-09-12       Impact factor: 3.493

  4 in total

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