Literature DB >> 24590225

Efficacy of brain-computer interface-driven neuromuscular electrical stimulation for chronic paresis after stroke.

Masahiko Mukaino1, Takashi Ono, Keiichiro Shindo, Toshiyuki Fujiwara, Tetsuo Ota, Akio Kimura, Meigen Liu, Junichi Ushiba.   

Abstract

OBJECTIVE: Brain computer interface technology is of great interest to researchers as a potential therapeutic measure for people with severe neurological disorders. The aim of this study was to examine the efficacy of brain computer interface, by comparing conventional neuromuscular electrical stimulation and brain computer interface-driven neuromuscular electrical stimulation, using an A-B-A-B withdrawal single-subject design.
METHODS: A 38-year-old male with severe hemiplegia due to a putaminal haemorrhage participated in this study. The design involved 2 epochs. In epoch A, the patient attempted to open his fingers during the application of neuromuscular electrical stimulation, irrespective of his actual brain activity. In epoch B, neuromuscular electrical stimulation was applied only when a significant motor-related cortical potential was observed in the electroencephalogram.
RESULTS: The subject initially showed diffuse functional magnetic resonance imaging activation and small electro-encephalogram responses while attempting finger movement. Epoch A was associated with few neurological or clinical signs of improvement. Epoch B, with a brain computer interface, was associated with marked lateralization of electroencephalogram (EEG) and blood oxygenation level dependent responses. Voluntary electromyogram (EMG) activity, with significant EEG-EMG coherence, was also prompted. Clinical improvement in upper-extremity function and muscle tone was observed.
CONCLUSION: These results indicate that self-directed training with a brain computer interface may induce activity- dependent cortical plasticity and promote functional recovery. This preliminary clinical investigation encourages further research using a controlled design.

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Mesh:

Year:  2014        PMID: 24590225     DOI: 10.2340/16501977-1785

Source DB:  PubMed          Journal:  J Rehabil Med        ISSN: 1650-1977            Impact factor:   2.912


  28 in total

1.  Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface.

Authors:  Natalie Mrachacz-Kersting; Ning Jiang; Andrew James Thomas Stevenson; Imran Khan Niazi; Vladimir Kostic; Aleksandra Pavlovic; Sasa Radovanovic; Milica Djuric-Jovicic; Federica Agosta; Kim Dremstrup; Dario Farina
Journal:  J Neurophysiol       Date:  2015-12-30       Impact factor: 2.714

2.  BCI-FES: could a new rehabilitation device hold fresh promise for stroke patients?

Authors:  Brittany M Young; Justin Williams; Vivek Prabhakaran
Journal:  Expert Rev Med Devices       Date:  2014-07-25       Impact factor: 3.166

3.  On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study.

Authors:  Anna Zulauf-Czaja; Manaf K H Al-Taleb; Mariel Purcell; Nina Petric-Gray; Jennifer Cloughley; Aleksandra Vuckovic
Journal:  J Neuroeng Rehabil       Date:  2021-02-25       Impact factor: 4.262

4.  Relief of neuropathic pain after spinal cord injury by brain-computer interface training.

Authors:  Naoki Yoshida; Yasunari Hashimoto; Mio Shikota; Tetsuo Ota
Journal:  Spinal Cord Ser Cases       Date:  2016-10-27

5.  EEG-Based Brain Network Analysis of Chronic Stroke Patients After BCI Rehabilitation Training.

Authors:  Gege Zhan; Shugeng Chen; Yanyun Ji; Ying Xu; Zuoting Song; Junkongshuai Wang; Lan Niu; Jianxiong Bin; Xiaoyang Kang; Jie Jia
Journal:  Front Hum Neurosci       Date:  2022-06-27       Impact factor: 3.473

6.  Brain-controlled functional electrical stimulation therapy for gait rehabilitation after stroke: a safety study.

Authors:  Colin M McCrimmon; Christine E King; Po T Wang; Steven C Cramer; Zoran Nenadic; An H Do
Journal:  J Neuroeng Rehabil       Date:  2015-07-11       Impact factor: 4.262

7.  Dose-response relationships using brain-computer interface technology impact stroke rehabilitation.

Authors:  Brittany M Young; Zack Nigogosyan; Léo M Walton; Alexander Remsik; Jie Song; Veena A Nair; Mitchell E Tyler; Dorothy F Edwards; Kristin Caldera; Justin A Sattin; Justin C Williams; Vivek Prabhakaran
Journal:  Front Hum Neurosci       Date:  2015-06-23       Impact factor: 3.169

8.  Brain-computer interface with somatosensory feedback improves functional recovery from severe hemiplegia due to chronic stroke.

Authors:  Takashi Ono; Keiichiro Shindo; Kimiko Kawashima; Naoki Ota; Mari Ito; Tetsuo Ota; Masahiko Mukaino; Toshiyuki Fujiwara; Akio Kimura; Meigen Liu; Junichi Ushiba
Journal:  Front Neuroeng       Date:  2014-07-07

9.  Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain-computer interface device.

Authors:  Brittany Mei Young; Zack Nigogosyan; Alexander Remsik; Léo M Walton; Jie Song; Veena A Nair; Scott W Grogan; Mitchell E Tyler; Dorothy Farrar Edwards; Kristin Caldera; Justin A Sattin; Justin C Williams; Vivek Prabhakaran
Journal:  Front Neuroeng       Date:  2014-07-08

10.  Case report: post-stroke interventional BCI rehabilitation in an individual with preexisting sensorineural disability.

Authors:  Brittany M Young; Zack Nigogosyan; Veena A Nair; Léo M Walton; Jie Song; Mitchell E Tyler; Dorothy F Edwards; Kristin Caldera; Justin A Sattin; Justin C Williams; Vivek Prabhakaran
Journal:  Front Neuroeng       Date:  2014-06-24
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