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Robot-assisted assessment of muscle strength.
Toigo, Marco; Flück, Martin; Riener, Robert; Klamroth-Marganska, Verena.
Afiliación
  • Toigo M; Laboratory for Muscle Plasticity, Balgrist University Hospital, University of Zurich, Zurich, Switzerland. marco.toigo@oym.ch.
  • Flück M; Laboratory for Muscle Plasticity, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
  • Riener R; Sensory-Motor Systems Lab, Department of Health Sciences and Technology ETH Zurich, Zurich, Switzerland.
  • Klamroth-Marganska V; Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
J Neuroeng Rehabil ; 14(1): 103, 2017 10 11.
Article en En | MEDLINE | ID: mdl-29020968
Impairment of neuromuscular function in neurological disorders leads to reductions in muscle force, which may lower quality of life. Rehabilitation robots that are equipped with sensors are able to quantify the extent of muscle force impairment and to monitor a patient during the process of neurorehabilitation with sensitive and objective assessment methods. In this article, we provide an overview of fundamental aspects of muscle function and how the corresponding variables can be quantified by means of meaningful robotic assessments that are primarily oriented towards upper limb neurorehabilitation. We discuss new concepts for the assessment of muscle function, and present an overview of the currently available systems for upper limb measurements. These considerations culminate in practical recommendations and caveats for the rational quantification of force magnitude, force direction, moment of a force, impulse, critical force (neuromuscular fatigue threshold) and state and trait levels of fatigue.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Robótica / Fuerza Muscular Tipo de estudio: Guideline Aspecto: Patient_preference Límite: Humans Idioma: En Revista: J Neuroeng Rehabil Asunto de la revista: ENGENHARIA BIOMEDICA / NEUROLOGIA / REABILITACAO Año: 2017 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Robótica / Fuerza Muscular Tipo de estudio: Guideline Aspecto: Patient_preference Límite: Humans Idioma: En Revista: J Neuroeng Rehabil Asunto de la revista: ENGENHARIA BIOMEDICA / NEUROLOGIA / REABILITACAO Año: 2017 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido