Adaptive algorithm for gait segmentation using a single IMU in the thigh pocket (2022)
- Authors:
- USP affiliated authors: TERRA, MARCO HENRIQUE - EESC ; SIQUEIRA, ADRIANO ALMEIDA GONÇALVES - EESC ; GARCIA, FRANCISCO AMBROSIO - EESC ; IBARRA, JUAN CARLOS PEREZ - EESC
- Unidade: EESC
- DOI: 10.1109/JSEN.2022.3177951
- Subjects: ALGORITMOS; APRENDIZADO COMPUTACIONAL; PROCESSOS DE MARKOV; ENGENHARIA MECÂNICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway, NJ, USA
- Date published: 2022
- Source:
- Título: IEEE Sensors Journal
- ISSN: 1530-437X
- Volume/Número/Paginação/Ano: v. 22, n. 3, p. 13251-13261, July 2022
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
GARCIA, Francisco A et al. Adaptive algorithm for gait segmentation using a single IMU in the thigh pocket. IEEE Sensors Journal, v. 22, n. 3, p. 13251-13261, 2022Tradução . . Disponível em: https://doi.org/10.1109/JSEN.2022.3177951. Acesso em: 02 out. 2024. -
APA
Garcia, F. A., Pérez Ibarra, J. C., Terra, M. H., & Siqueira, A. A. G. (2022). Adaptive algorithm for gait segmentation using a single IMU in the thigh pocket. IEEE Sensors Journal, 22( 3), 13251-13261. doi:10.1109/JSEN.2022.3177951 -
NLM
Garcia FA, Pérez Ibarra JC, Terra MH, Siqueira AAG. Adaptive algorithm for gait segmentation using a single IMU in the thigh pocket [Internet]. IEEE Sensors Journal. 2022 ; 22( 3): 13251-13261.[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/JSEN.2022.3177951 -
Vancouver
Garcia FA, Pérez Ibarra JC, Terra MH, Siqueira AAG. Adaptive algorithm for gait segmentation using a single IMU in the thigh pocket [Internet]. IEEE Sensors Journal. 2022 ; 22( 3): 13251-13261.[citado 2024 out. 02 ] Available from: https://doi.org/10.1109/JSEN.2022.3177951 - Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects
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Informações sobre o DOI: 10.1109/JSEN.2022.3177951 (Fonte: oaDOI API)
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