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Computer-assisted approaches for measuring, segmenting, and analyzing functional upper extremity movement: a narrative review of the current state, limitations, and future directions.
Jackson, Kyle L; Duric, Zoran; Engdahl, Susannah M; Santago Ii, Anthony C; DeStefano, Secili; Gerber, Lynn H.
Afiliación
  • Jackson KL; Department of Computer Science, George Mason University, Fairfax, VA, United States.
  • Duric Z; MITRE Corporation, McLean, VA, United States.
  • Engdahl SM; Department of Computer Science, George Mason University, Fairfax, VA, United States.
  • Santago Ii AC; Center for Adaptive Systems and Brain-Body Interactions, George Mason University, Fairfax, VA, United States.
  • DeStefano S; Center for Adaptive Systems and Brain-Body Interactions, George Mason University, Fairfax, VA, United States.
  • Gerber LH; Department of Bioengineering, George Mason University, Fairfax, VA, United States.
Front Rehabil Sci ; 4: 1130847, 2023.
Article en En | MEDLINE | ID: mdl-37113748
ABSTRACT
The analysis of functional upper extremity (UE) movement kinematics has implications across domains such as rehabilitation and evaluating job-related skills. Using movement kinematics to quantify movement quality and skill is a promising area of research but is currently not being used widely due to issues associated with cost and the need for further methodological validation. Recent developments by computationally-oriented research communities have resulted in potentially useful methods for evaluating UE function that may make kinematic analyses easier to perform, generally more accessible, and provide more objective information about movement quality, the importance of which has been highlighted during the COVID-19 pandemic. This narrative review provides an interdisciplinary perspective on the current state of computer-assisted methods for analyzing UE kinematics with a specific focus on how to make kinematic analyses more accessible to domain experts. We find that a variety of methods exist to more easily measure and segment functional UE movement, with a subset of those methods being validated for specific applications. Future directions include developing more robust methods for measurement and segmentation, validating these methods in conjunction with proposed kinematic outcome measures, and studying how to integrate kinematic analyses into domain expert workflows in a way that improves outcomes.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Rehabil Sci Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Rehabil Sci Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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