Your browser doesn't support javascript.
loading
Training with Agency-Inspired Feedback from an Instrumented Glove to Improve Functional Grasp Performance.
Liu, Mingxiao; Wilder, Samuel; Sanford, Sean; Saleh, Soha; Harel, Noam Y; Nataraj, Raviraj.
Afiliação
  • Liu M; Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
  • Wilder S; Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
  • Sanford S; Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
  • Saleh S; Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
  • Harel NY; Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
  • Nataraj R; Movement Control Rehabilitation (MOCORE) Laboratory, Altorfer Complex, Stevens Institute of Technology, Hoboken, NJ 07030, USA.
Sensors (Basel) ; 21(4)2021 Feb 07.
Article em En | MEDLINE | ID: mdl-33562342
ABSTRACT
Sensory feedback from wearables can be effective to learn better movement through enhanced information and engagement. Facilitating greater user cognition during movement practice is critical to accelerate gains in motor function during rehabilitation following brain or spinal cord trauma. This preliminary study presents an approach using an instrumented glove to leverage sense of agency, or perception of control, to provide training feedback for functional grasp. Seventeen able-bodied subjects underwent training and testing with a custom-built sensor glove prototype from our laboratory. The glove utilizes onboard force and flex sensors to provide inputs to an artificial neural network that predicts achievement of "secure" grasp. Onboard visual and audio feedback was provided during training with progressively shorter time delay to induce greater agency by intentional binding, or perceived compression in time between an action (grasp) and sensory consequence (feedback). After training, subjects demonstrated a significant reduction (p < 0.05) in movement pathlength and completion time for a functional task involving grasp-move-place of a small object. Future work will include a model-based algorithm to compute secure grasp, virtual reality immersion, and testing with clinical populations.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Força da Mão / Mãos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Força da Mão / Mãos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article