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Hum Mov Sci ; 30(5): 966-75, 2011 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-21195495

RESUMO

The aim of the study was to train and test support vector machines (SVM) and self-organizing maps (SOM) to correctly classify gait patterns before, during and after complete leg exhaustion by isokinetic leg exercises. Ground reaction forces were derived for 18 gait cycles on 9 adult participants. Immediately before the trials 7-12, participants were required to completely exhaust their calves with the aid of additional weights (44.4±8.8kg). Data were analyzed using: (a) the time courses directly and (b) only the deviations from each individual's calculated average gait pattern. On an inter-individual level the person recognition of the gait patterns was 100% realizable. Fatigue recognition was also highly probable at 98.1%. Additionally, applied SOMs allowed an alternative visualization of the development of fatigue in the gait patterns over the progressive fatiguing exercise regimen.


Assuntos
Marcha/fisiologia , Fadiga Muscular/fisiologia , Máquina de Vetores de Suporte , Adulto , Fenômenos Biomecânicos , Humanos , Individualidade , Masculino , Dinâmica não Linear , Reconhecimento Automatizado de Padrão , Levantamento de Peso/fisiologia , Adulto Jovem
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