Multimodal Head-Mounted Virtual-Reality Brain-Computer Interface for Stroke Rehabilitation A Clinical Case Study with REINVENT
Rehabilitation after stroke requires the exploitation of active movement by the patient in order to efficiently re-train the affected side. Individuals with severe stroke cannot benefit from many training solutions since they have paresis and/or spasticity, limiting volitional movement. Nonetheless,...
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Published in | Virtual, Augmented and Mixed Reality. Multimodal Interaction pp. 165 - 179 |
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Main Authors | , , , , , |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
2019
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Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
ISBN | 9783030216061 3030216063 |
ISSN | 0302-9743 1611-3349 |
DOI | 10.1007/978-3-030-21607-8_13 |
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Abstract | Rehabilitation after stroke requires the exploitation of active movement by the patient in order to efficiently re-train the affected side. Individuals with severe stroke cannot benefit from many training solutions since they have paresis and/or spasticity, limiting volitional movement. Nonetheless, research has shown that individuals with severe stroke may have modest benefits from action observation, virtual reality, and neurofeedback from brain-computer interfaces (BCIs). In this study, we combined the principles of action observation in VR together with BCI neurofeedback for stroke rehabilitation to try to elicit optimal rehabilitation gains. Here, we illustrate the development of the REINVENT platform, which takes post-stroke brain signals indicating an attempt to move and drives a virtual avatar arm, providing patient-driven action observation in head-mounted VR. We also present a longitudinal case study with a single individual to demonstrate the feasibility and potentially efficacy of the REINVENT system. |
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AbstractList | Rehabilitation after stroke requires the exploitation of active movement by the patient in order to efficiently re-train the affected side. Individuals with severe stroke cannot benefit from many training solutions since they have paresis and/or spasticity, limiting volitional movement. Nonetheless, research has shown that individuals with severe stroke may have modest benefits from action observation, virtual reality, and neurofeedback from brain-computer interfaces (BCIs). In this study, we combined the principles of action observation in VR together with BCI neurofeedback for stroke rehabilitation to try to elicit optimal rehabilitation gains. Here, we illustrate the development of the REINVENT platform, which takes post-stroke brain signals indicating an attempt to move and drives a virtual avatar arm, providing patient-driven action observation in head-mounted VR. We also present a longitudinal case study with a single individual to demonstrate the feasibility and potentially efficacy of the REINVENT system. |
Author | Vourvopoulos, Athanasios Marin-Pardo, Octavio Neureither, Meghan Saldana, David Jahng, Esther Liew, Sook-Lei |
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Copyright | Springer Nature Switzerland AG 2019 |
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DOI | 10.1007/978-3-030-21607-8_13 |
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Editor | Fragomeni, Gino Chen, Jessie Y.C. |
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Snippet | Rehabilitation after stroke requires the exploitation of active movement by the patient in order to efficiently re-train the affected side. Individuals with... |
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StartPage | 165 |
SubjectTerms | Brain-computer interfaces Stroke rehabilitation Virtual reality |
Subtitle | A Clinical Case Study with REINVENT |
Title | Multimodal Head-Mounted Virtual-Reality Brain-Computer Interface for Stroke Rehabilitation |
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