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Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson's disease.
Ripic, Zachary; Signorile, Joseph F; Best, Thomas M; Jacobs, Kevin A; Nienhuis, Mitch; Whitelaw, Cole; Moenning, Caden; Eltoukhy, Moataz.
Afiliação
  • Ripic Z; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Sports Medicine Institute, University of Miami Miller School of Medicine, Miami, FL, United States.
  • Signorile JF; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Center on Aging, University of Miami Miller School of Medicine, Miami, FL, United States.
  • Best TM; Sports Medicine Institute, University of Miami Miller School of Medicine, Miami, FL, United States; Department of Orthopaedics, University of Miami Miller School of Medicine, Miami, FL, United States.
  • Jacobs KA; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States.
  • Nienhuis M; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States.
  • Whitelaw C; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States.
  • Moenning C; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States.
  • Eltoukhy M; Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Department of Industrial and Systems Engineering, University of Miami, Miami, FL, United States. Electronic address: meltoukhy@miami.edu.
J Biomech ; 155: 111645, 2023 06.
Article em En | MEDLINE | ID: mdl-37216895
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Parkinson / Inteligência Artificial Tipo de estudo: Prognostic_studies Limite: Adult / Aged / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Parkinson / Inteligência Artificial Tipo de estudo: Prognostic_studies Limite: Adult / Aged / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article