Literature DB >> 29689307

Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance.

Tiffany Corbet1, Iñaki Iturrate2, Michael Pereira2, Serafeim Perdikis2, José Del R Millán2.   

Abstract

Motor imagery (MI) has been largely studied as a way to enhance motor learning and to restore motor functions. Although it is agreed that users should emphasize kinesthetic imagery during MI, recordings of MI brain patterns are not sufficiently reliable for many subjects. It has been suggested that the usage of somatosensory feedback would be more suitable than standardly used visual feedback to enhance MI brain patterns. However, somatosensory feedback should not interfere with the recorded MI brain pattern. In this study we propose a novel feedback modality to guide subjects during MI based on sensory threshold neuromuscular electrical stimulation (St-NMES). St-NMES depolarizes sensory and motor axons without eliciting any muscular contraction. We hypothesize that St-NMES does not induce detectable ERD brain patterns and fosters MI performance. Twelve novice subjects were included in a cross-over design study. We recorded their EEG, comparing St-NMES with visual feedback during MI or resting tasks. We found that St-NMES not only induced significantly larger desynchronization over sensorimotor areas (p<0.05) but also significantly enhanced MI brain connectivity patterns. Moreover, classification accuracy and stability were significantly higher with St-NMES. Importantly, St-NMES alone did not induce detectable artifacts, but rather the changes in the detected patterns were due to an increased MI performance. Our findings indicate that St-NMES is a promising feedback in order to foster MI performance and cold be used for BMI online applications.
Copyright © 2018 Elsevier Inc. All rights reserved.

Keywords:  Brain-machine interface; EEG imaging; Kinesthetic imagery; Motor imagery; Sensory electrical stimulation

Mesh:

Year:  2018        PMID: 29689307     DOI: 10.1016/j.neuroimage.2018.04.005

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  12 in total

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2.  Volunteers' concerns about facial neuromuscular electrical stimulation.

Authors:  Themis Nikolas Efthimiou; Paul H P Hanel; Sebastian Korb
Journal:  BMC Psychol       Date:  2022-05-07

3.  Spatial-temporal aspects of continuous EEG-based neurorobotic control.

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Journal:  J Neural Eng       Date:  2020-11-11       Impact factor: 5.379

4.  Investigation of Optimal Afferent Feedback Modality for Inducing Neural Plasticity with A Self-Paced Brain-Computer Interface.

Authors:  Mads Jochumsen; Sylvain Cremoux; Lucien Robinault; Jimmy Lauber; Juan Carlos Arceo; Muhammad Samran Navid; Rasmus Wiberg Nedergaard; Usman Rashid; Heidi Haavik; Imran Khan Niazi
Journal:  Sensors (Basel)       Date:  2018-11-03       Impact factor: 3.576

5.  Pathway-specific modulatory effects of neuromuscular electrical stimulation during pedaling in chronic stroke survivors.

Authors:  Shi-Chun Bao; Wing-Cheong Leung; Vincent C K Cheung; Ping Zhou; Kai-Yu Tong
Journal:  J Neuroeng Rehabil       Date:  2019-11-19       Impact factor: 4.262

6.  Characterization of kinesthetic motor imagery compared with visual motor imageries.

Authors:  Yu Jin Yang; Eun Jeong Jeon; June Sic Kim; Chun Kee Chung
Journal:  Sci Rep       Date:  2021-02-12       Impact factor: 4.379

7.  Peripheral Electrical Stimulation Modulates Cortical Beta-Band Activity.

Authors:  Laura J Arendsen; Robert Guggenberger; Manuela Zimmer; Tobias Weigl; Alireza Gharabaghi
Journal:  Front Neurosci       Date:  2021-03-25       Impact factor: 4.677

8.  Effect of Cervical Transcutaneous Spinal Cord Stimulation on Sensorimotor Cortical Activity during Upper-Limb Movements in Healthy Individuals.

Authors:  Ciarán McGeady; Monzurul Alam; Yong-Ping Zheng; Aleksandra Vučković
Journal:  J Clin Med       Date:  2022-02-17       Impact factor: 4.241

9.  The Effects of Sensory Threshold Somatosensory Electrical Stimulation on Users With Different MI-BCI Performance.

Authors:  Long Chen; Lei Zhang; Zhongpeng Wang; Bin Gu; Xin Zhang; Dong Ming
Journal:  Front Neurosci       Date:  2022-06-17       Impact factor: 5.152

Review 10.  Challenges and Opportunities for the Future of Brain-Computer Interface in Neurorehabilitation.

Authors:  Colin Simon; David A E Bolton; Niamh C Kennedy; Surjo R Soekadar; Kathy L Ruddy
Journal:  Front Neurosci       Date:  2021-07-02       Impact factor: 4.677

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