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NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework.
Cashaback, Joshua G A; Allen, Jessica L; Chou, Amber Hsiao-Yang; Lin, David J; Price, Mark A; Secerovic, Natalija K; Song, Seungmoon; Zhang, Haohan; Miller, Haylie L.
Afiliação
  • Cashaback JGA; Biomedical Engineering, Mechanical Engineering, Kinesiology and Applied Physiology, Biome chanics and Movement Science Program, Interdisciplinary Neuroscience Graduate Program, University of Delaware, 540 S College Ave, Newark, DE, 19711, USA. cashabackjga@gmail.com.
  • Allen JL; Department of Mechanical Engineering, University of Florida, Gainesville, USA.
  • Chou AH; Electrical and Computer Engineering, University of Washington, Seattle, USA.
  • Lin DJ; Division of Neurocritical Care and Stroke Service, Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
  • Price MA; Department of Veterans Affairs, Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Providence, USA.
  • Secerovic NK; Department of Mechanical and Industrial Engineering, Department of Kinesiology, University of Massachusetts Amherst, Amherst, USA.
  • Song S; School of Electrical Engineering, The Mihajlo Pupin Institute, University of Belgrade, Belgrade, Serbia.
  • Zhang H; Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems ETH Zürich, Zurich, Switzerland.
  • Miller HL; Mechanical and Industrial Engineering, Northeastern University, Boston, USA.
J Neuroeng Rehabil ; 21(1): 23, 2024 02 13.
Article em En | MEDLINE | ID: mdl-38347597
ABSTRACT
In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pessoas com Deficiência / Reabilitação Neurológica Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pessoas com Deficiência / Reabilitação Neurológica Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article