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Combining virtual reality with a biomechanical model to improve Parkinson’s movement: solution proposal and reference learning data

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Detalhes bibliográficos
Resumo:Parkinson’s disease imposes a substantial global health burden and causes severe motor impairments that compromise the quality of life. Virtual reality-based mirror training (VRMT) has the potential to improve motor function through immersive action observation, motor imagery, and real-time feedback. This study aims to propose a novel VRMT personalized for Parkinson rehabilitation and present reference learning data from a biomechanical model obtained from twelve healthy individuals performing the activities of lifting the leg, arising from a chair, and touching the nose included in the Movement Disorder Society Unified Parkinson’s Disease Rating Scale. The results reveal insights on the maintenance of balance when arising from a chair through linear variation of center of mass, minimal hand position shaking and thus minimal tremors during activity of touching the nose, and high maximum foot velocity of approximately 0.79±0.26 1/s during activity of lifting the leg. The data collected accurately represents the expected healthy execution and related variability for each activity, serving as a learning reference for the future development of VRMT.
Autores principais:Henriques, Ana
Outros Autores:Pinheiro, Cristiana; Santos, Cristina P.
Assunto:Action observation Biomechanics Mirror therapy Motor execution Motor imagery Real-time feedbac Parkinson’s disease Real-time Feedback Engenharia e Tecnologia::Engenharia Médica Saúde de qualidade
Ano:2024
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Parkinson’s disease imposes a substantial global health burden and causes severe motor impairments that compromise the quality of life. Virtual reality-based mirror training (VRMT) has the potential to improve motor function through immersive action observation, motor imagery, and real-time feedback. This study aims to propose a novel VRMT personalized for Parkinson rehabilitation and present reference learning data from a biomechanical model obtained from twelve healthy individuals performing the activities of lifting the leg, arising from a chair, and touching the nose included in the Movement Disorder Society Unified Parkinson’s Disease Rating Scale. The results reveal insights on the maintenance of balance when arising from a chair through linear variation of center of mass, minimal hand position shaking and thus minimal tremors during activity of touching the nose, and high maximum foot velocity of approximately 0.79±0.26 1/s during activity of lifting the leg. The data collected accurately represents the expected healthy execution and related variability for each activity, serving as a learning reference for the future development of VRMT.