Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/115309
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Biomedical Engineering | - |
dc.creator | Lin, L | - |
dc.creator | Qing, W | - |
dc.creator | Zheng, Z | - |
dc.creator | Poon, W | - |
dc.creator | Guo, SS | - |
dc.creator | Zhang, S | - |
dc.creator | Hu, XL | - |
dc.date.accessioned | 2025-09-19T03:24:01Z | - |
dc.date.available | 2025-09-19T03:24:01Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/115309 | - |
dc.language.iso | en | en_US |
dc.publisher | Frontiers Research Foundation | en_US |
dc.rights | © 2024 Lin, Qing, Zheng, Poon, Guo, Zhang and Hu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | en_US |
dc.rights | The following publication Lin, L., Qing, W., Zheng, Z., Poon, W., Guo, S., Zhang, S., & Hu, X. (2024). Somatosensory integration in robot-assisted motor restoration post-stroke. Frontiers in Aging Neuroscience, 16, 1491678 is available at https://doi.org/10.3389/fnagi.2024.1491678. | en_US |
dc.subject | Movement recovery | en_US |
dc.subject | Neuroimaging | en_US |
dc.subject | Neuromodulation | en_US |
dc.subject | Rehabilitation | en_US |
dc.subject | Robot | en_US |
dc.subject | Sensorimotor integration | en_US |
dc.subject | Somatosensory stimulation | en_US |
dc.subject | Stroke | en_US |
dc.subject | Article | en_US |
dc.subject | Berg balance scale | en_US |
dc.subject | Blood flow velocity | en_US |
dc.subject | Brain blood flow | en_US |
dc.subject | Central nervous system | en_US |
dc.subject | Cerebrovascular accident | en_US |
dc.subject | Deltoid muscle | en_US |
dc.subject | Dorsolateral prefrontal cortex | en_US |
dc.subject | Echography | en_US |
dc.subject | Electroencephalography | en_US |
dc.subject | Electromyography | en_US |
dc.subject | Electrostimulation | en_US |
dc.subject | Entropy | en_US |
dc.subject | Feedback system | en_US |
dc.subject | Functional connectivity | en_US |
dc.subject | Health care quality | en_US |
dc.subject | Hemodynamics | en_US |
dc.subject | Human | en_US |
dc.subject | Integration | en_US |
dc.subject | Learning | en_US |
dc.subject | Mean arterial pressure | en_US |
dc.subject | Motor evoked potential | en_US |
dc.subject | Motor performance | en_US |
dc.subject | Motor restoration | en_US |
dc.subject | Nerve cell plasticity | en_US |
dc.subject | Nerve stimulation | en_US |
dc.subject | Neuroimaging | en_US |
dc.subject | Neuromodulation | en_US |
dc.subject | Neuromuscular electrical stimulation | en_US |
dc.subject | Neurorehabilitation | en_US |
dc.subject | Nociception | en_US |
dc.subject | Optogenetics | en_US |
dc.subject | Primary motor cortex | en_US |
dc.subject | Protocol | en_US |
dc.subject | Pulsatility index | en_US |
dc.subject | Rehabilitation medicine | en_US |
dc.subject | Robot assisted surgery | en_US |
dc.subject | Sensorimotor integration | en_US |
dc.subject | Sensory cortex | en_US |
dc.subject | Signal noise ratio | en_US |
dc.subject | Somatosensory cortex | en_US |
dc.subject | Somatosensory stimulation | en_US |
dc.subject | Somatosensory system | en_US |
dc.subject | Spinal cord injury | en_US |
dc.subject | Stroke rehabilitation | en_US |
dc.subject | Tactile stimulation | en_US |
dc.subject | Telerehabilitation | en_US |
dc.subject | Training | en_US |
dc.subject | Transcranial direct current stimulation | en_US |
dc.subject | Transcranial magnetic stimulation | en_US |
dc.title | Somatosensory integration in robot-assisted motor restoration post-stroke | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 16 | - |
dc.identifier.doi | 10.3389/fnagi.2024.1491678 | - |
dcterms.abstract | Disruption of somatosensorimotor integration (SMI) after stroke is a significant obstacle to achieving precise motor restoration. Integrating somatosensory input into motor relearning to reconstruct SMI is critical during stroke rehabilitation. However, current robotic approaches focus primarily on precise control of repetitive movements and rarely effectively engage and modulate somatosensory responses, which impedes motor rehabilitation that relies on SMI. This article discusses how to effectively regulate somatosensory feedback from target muscles through peripheral and central neuromodulatory stimulations based on quantitatively measured somatosensory responses in real time during robot-assisted rehabilitation after stroke. Further development of standardized recording protocols and diagnostic databases of quantitative neuroimaging features in response to post-stroke somatosensory stimulations for real-time precise detection, and optimized combinations of peripheral somatosensory stimulations with robot assistance and central nervous neuromodulation are needed to enhance the recruitment of targeted ascending neuromuscular pathways in robot-assisted training, aiming to achieve precise muscle control and integrated somatosensorimotor functions, thereby improving long-term neurorehabilitation after stroke. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Frontiers in aging neuroscience, 6 Nov. 2024, v. 16, 1491678 | - |
dcterms.isPartOf | Frontiers in aging neuroscience | - |
dcterms.issued | 2024-11 | - |
dc.identifier.scopus | 2-s2.0-85209570808 | - |
dc.identifier.eissn | 1663-4365 | - |
dc.identifier.artn | 1491678 | - |
dc.description.validate | 202509 bchy | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | CDCF_2024-2025 | en_US |
dc.description.fundingSource | RGC | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by the University Grants Committee Research Grants Council, Hong Kong (GRF15207120, SRFS2122-5S04, GRF15304322, and GRF15304823), the Hong Kong Polytechnic University (1-ZVVP and 1-CD74), and the Innovation and Technology Fund \u2013 Guangdong-Hong Kong Technology Cooperation Funding Scheme (ITF-TCFS) (GHP/260/22SZ). | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
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