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 inVirtual, Augmented and Mixed Reality. Multimodal Interaction pp. 165 - 179
Main Authors Vourvopoulos, Athanasios, Marin-Pardo, Octavio, Neureither, Meghan, Saldana, David, Jahng, Esther, Liew, Sook-Lei
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2019
SeriesLecture Notes in Computer Science
Subjects
Online AccessGet full text
ISBN9783030216061
3030216063
ISSN0302-9743
1611-3349
DOI10.1007/978-3-030-21607-8_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.
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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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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