Research Topic

Human Machine Interface-based Neuromodulation Solutions for Neurorehabilitation

About this Research Topic

Millions of people suffer from central nervous diseases such as stroke, spinal cord injuries, and cerebral palsy worldwide. The quality of life for these survivors is considerably reduced due to functional disabilities. Despite traditional therapies, new interventions based on neuromodulation techniques and human-machine interfaces such as brain-computer interfaces (BCI), transcranial magnetic stimulations (TMS), transcranial direct current stimulations (tDCS), functional electrical stimulations (FES), as well as neuroimaging technologies including functional magnetic resonance (fMRI) and functional near-infrared spectroscopy (fNIRS) are being used to improve neurorehabilitation of survivors. Rehabilitation robots and/or FES combined with neuromodulation (BCI/TMS/tDCS) and neuroimaging technologies have been proved to be a promising strategy for neurorehabilitation. Also, emerging machine learning and deep learning algorithms may extract more meaningful information from EEG/EMG/fNIRS signals related to motion intention, which is extremely important in neurorehabilitation. Clinically, we need more evidence quantitatively exploring the mechanism and performance of the novel protocols.

This Research Topic aims to discuss the neuromodulation techniques of human-machine interfaces in the field of neurorehabilitation and exploring how these modulation techniques affect human brains via neuroimaging methods. State-of-the-art interdisciplinary research in neuromodulation techniques (BCI/TMS/tDCS), as well as neuroimage methodologies (fMRI/fNIRS) in the field of neurorehabilitation, will be involved in this Research Topic. New methods, mechanisms, and applications of these techniques in neurorehabilitation will be the pipeline of this Topic. Specifically, innovative approaches by translating current research results into clinical applications are of great interest. The main objective of this Research Topic is to discuss the advantages and limitations of currently used solutions and suggest possible innovations in the field of Neurorehabilitation.

We welcome investigators to contribute original research articles, case reports as well as reviews that will promote a better understanding of the neuromodulation techniques of human-machine interfacing in neurorehabilitation. Potential topics include, but are not limited to:

- New paradigms and algorithms of BCI in neurorehabilitation
- Clinical trials with neuromodulation techniques of human-machine interfaces in neurorehabilitation
- Clinical applications of neuromodulation techniques in neurorehabilitation
- BCI-triggered TMS/FES/tDCS in neurorehabilitation
- EMG based interfaces in neurorehabilitation


Keywords: Human Machine Interface, Neurorehabilitation, Brain computer interface, Neurological disorder, Neuromodulation


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Millions of people suffer from central nervous diseases such as stroke, spinal cord injuries, and cerebral palsy worldwide. The quality of life for these survivors is considerably reduced due to functional disabilities. Despite traditional therapies, new interventions based on neuromodulation techniques and human-machine interfaces such as brain-computer interfaces (BCI), transcranial magnetic stimulations (TMS), transcranial direct current stimulations (tDCS), functional electrical stimulations (FES), as well as neuroimaging technologies including functional magnetic resonance (fMRI) and functional near-infrared spectroscopy (fNIRS) are being used to improve neurorehabilitation of survivors. Rehabilitation robots and/or FES combined with neuromodulation (BCI/TMS/tDCS) and neuroimaging technologies have been proved to be a promising strategy for neurorehabilitation. Also, emerging machine learning and deep learning algorithms may extract more meaningful information from EEG/EMG/fNIRS signals related to motion intention, which is extremely important in neurorehabilitation. Clinically, we need more evidence quantitatively exploring the mechanism and performance of the novel protocols.

This Research Topic aims to discuss the neuromodulation techniques of human-machine interfaces in the field of neurorehabilitation and exploring how these modulation techniques affect human brains via neuroimaging methods. State-of-the-art interdisciplinary research in neuromodulation techniques (BCI/TMS/tDCS), as well as neuroimage methodologies (fMRI/fNIRS) in the field of neurorehabilitation, will be involved in this Research Topic. New methods, mechanisms, and applications of these techniques in neurorehabilitation will be the pipeline of this Topic. Specifically, innovative approaches by translating current research results into clinical applications are of great interest. The main objective of this Research Topic is to discuss the advantages and limitations of currently used solutions and suggest possible innovations in the field of Neurorehabilitation.

We welcome investigators to contribute original research articles, case reports as well as reviews that will promote a better understanding of the neuromodulation techniques of human-machine interfacing in neurorehabilitation. Potential topics include, but are not limited to:

- New paradigms and algorithms of BCI in neurorehabilitation
- Clinical trials with neuromodulation techniques of human-machine interfaces in neurorehabilitation
- Clinical applications of neuromodulation techniques in neurorehabilitation
- BCI-triggered TMS/FES/tDCS in neurorehabilitation
- EMG based interfaces in neurorehabilitation


Keywords: Human Machine Interface, Neurorehabilitation, Brain computer interface, Neurological disorder, Neuromodulation


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 May 2021 Abstract
05 September 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 May 2021 Abstract
05 September 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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