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Augmented feedback modes during functional grasp training with an intelligent glove and virtual reality for persons with traumatic brain injury.
Liu, Mingxiao; Wilder, Samuel; Sanford, Sean; Glassen, Michael; Dewil, Sophie; Saleh, Soha; Nataraj, Raviraj.
Afiliação
  • Liu M; Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
  • Wilder S; Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ, United States.
  • Sanford S; Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
  • Glassen M; Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ, United States.
  • Dewil S; Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.
  • Saleh S; Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ, United States.
  • Nataraj R; Center for Mobility and Rehabilitation Engineering Research, Advanced Rehabilitation Neuroimaging Laboratory, Kessler Foundation, NJ, United States.
Front Robot AI ; 10: 1230086, 2023.
Article em En | MEDLINE | ID: mdl-38077451
ABSTRACT

Introduction:

Physical therapy is crucial to rehabilitating hand function needed for activities of daily living after neurological traumas such as traumatic brain injury (TBI). Virtual reality (VR) can motivate participation in motor rehabilitation therapies. This study examines how multimodal feedback in VR to train grasp-and-place function will impact the neurological and motor responses in TBI participants (n = 7) compared to neurotypicals (n = 13).

Methods:

We newly incorporated VR with our existing intelligent glove system to seamlessly enhance the augmented visual and audio feedback to inform participants about grasp security. We then assessed how multimodal feedback (audio plus visual cues) impacted electroencephalography (EEG) power, grasp-and-place task performance (motion pathlength, completion time), and electromyography (EMG) measures.

Results:

After training with multimodal feedback, electroencephalography (EEG) alpha power significantly increased for TBI and neurotypical groups. However, only the TBI group demonstrated significantly improved performance or significant shifts in EMG activity.

Discussion:

These results suggest that the effectiveness of motor training with augmented sensory feedback will depend on the nature of the feedback and the presence of neurological dysfunction. Specifically, adding sensory cues may better consolidate early motor learning when neurological dysfunction is present. Computerized interfaces such as virtual reality offer a powerful platform to personalize rehabilitative training and improve functional outcomes based on neuropathology.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Robot AI Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Robot AI Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos