Your browser doesn't support javascript.
loading
Development of a mathematical model that predicts optimal muscle activation patterns by using brief trains.
Ding, J; Wexler, A S; Binder-Macleod, S A.
Afiliação
  • Ding J; Interdisciplinary Graduate Program in Biomechanics and Movement Science, University of Delaware, Newark, Delaware 19716, USA.
J Appl Physiol (1985) ; 88(3): 917-25, 2000 Mar.
Article em En | MEDLINE | ID: mdl-10710386
ABSTRACT
Because muscles must be repetitively activated during functional electrical stimulation, it is desirable to identify the stimulation pattern that produces the most force. Previous experimental work has shown that the optimal pattern contains an initial high-frequency burst of pulses (i.e., an initial doublet or triplet) followed by a low, constant-frequency portion. Pattern optimization is particularly challenging, because a muscle's contractile characteristics and, therefore, the optimal pattern change under different physiological conditions and are different for each person. This work describes the continued development and testing of a mathematical model that predicts isometric forces from fresh and fatigued muscles in response to brief trains of electrical pulses. By use of this model and an optimization algorithm, stimulation patterns that produced maximum forces from each subject were identified.
Assuntos
Buscar no Google
Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Músculo Esquelético / Contração Isométrica / Modelos Biológicos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Appl Physiol (1985) Assunto da revista: FISIOLOGIA Ano de publicação: 2000 Tipo de documento: Article País de afiliação: Estados Unidos
Buscar no Google
Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Músculo Esquelético / Contração Isométrica / Modelos Biológicos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Appl Physiol (1985) Assunto da revista: FISIOLOGIA Ano de publicação: 2000 Tipo de documento: Article País de afiliação: Estados Unidos