Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns (2018)
- Authors:
- Autor USP: ERVILHA, ULYSSES FERNANDES - EACH
- Unidade: EACH
- DOI: 10.1123/jab.2017-0349
- Subjects: BIOMECÂNICA; CALÇADOS; CORRIDAS; RECONHECIMENTO DE PADRÕES; ELETROMIOGRAFIA
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Applied Biomechanics
- ISSN: 1065-8483
- Volume/Número/Paginação/Ano: online, p. 01-15, Aug. 2018
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
PIRES, Ricardo et al. Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns. Journal of Applied Biomechanics, p. 01-15, 2018Tradução . . Disponível em: https://doi.org/10.1123/jab.2017-0349. Acesso em: 27 dez. 2025. -
APA
Pires, R., Falcari, T., Campo, A. B., Pulcineli, B. C., Hamill, J., & Ervilha, U. F. (2018). Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns. Journal of Applied Biomechanics, 01-15. doi:10.1123/jab.2017-0349 -
NLM
Pires R, Falcari T, Campo AB, Pulcineli BC, Hamill J, Ervilha UF. Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns [Internet]. Journal of Applied Biomechanics. 2018 ; 01-15.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1123/jab.2017-0349 -
Vancouver
Pires R, Falcari T, Campo AB, Pulcineli BC, Hamill J, Ervilha UF. Using a support-vector machine algorithm to classify lower extremity EMG signals during running shod/unshod with different foot strike patterns [Internet]. Journal of Applied Biomechanics. 2018 ; 01-15.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1123/jab.2017-0349 - Effect of experimentally induced muscle pain on neuromuscular control of force production
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Informações sobre o DOI: 10.1123/jab.2017-0349 (Fonte: oaDOI API)
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