Real-time identification of gait events in impaired subjects using a single-IMU foot-mounted device (2020)
- Authors:
- USP affiliated authors: SIQUEIRA, ADRIANO ALMEIDA GONÇALVES - EESC ; IBARRA, JUAN CARLOS PEREZ - EESC
- Unidade: EESC
- DOI: 10.1109/JSEN.2019.2951923
- Subjects: ROBÓTICA; BIOMECÂNICA; MARCHA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ
- Date published: 2020
- Source:
- Título do periódico: IEEE Sensors Journal
- ISSN: 1558-1748
- Volume/Número/Paginação/Ano: v. 20, n.5, p. 2616-2624, Mar. 2020
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
PÉREZ IBARRA, Juan Carlos e SIQUEIRA, Adriano Almeida Gonçalves. Real-time identification of gait events in impaired subjects using a single-IMU foot-mounted device. IEEE Sensors Journal, v. 20, n. 5, p. 2616-2624, 2020Tradução . . Disponível em: https://doi.org/10.1109/JSEN.2019.2951923. Acesso em: 10 jun. 2024. -
APA
Pérez Ibarra, J. C., & Siqueira, A. A. G. (2020). Real-time identification of gait events in impaired subjects using a single-IMU foot-mounted device. IEEE Sensors Journal, 20( 5), 2616-2624. doi:10.1109/JSEN.2019.2951923 -
NLM
Pérez Ibarra JC, Siqueira AAG. Real-time identification of gait events in impaired subjects using a single-IMU foot-mounted device [Internet]. IEEE Sensors Journal. 2020 ; 20( 5): 2616-2624.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/JSEN.2019.2951923 -
Vancouver
Pérez Ibarra JC, Siqueira AAG. Real-time identification of gait events in impaired subjects using a single-IMU foot-mounted device [Internet]. IEEE Sensors Journal. 2020 ; 20( 5): 2616-2624.[citado 2024 jun. 10 ] Available from: https://doi.org/10.1109/JSEN.2019.2951923 - Identification of gait events in healthy subjects and with parkinson’s disease using inertial sensors: an adaptive unsupervised learning approach
- Real-time identification of impaired gait phases using a single foot-mounted inertial sensor: review and feasibility study
- Identification of gait events in healthy and parkinson’s disease subjects using inertial sensors: a supervised learning approach
- Adaptive gait phase segmentation based on the time-varying identification of the ankle dynamics: technique and simulation results
- Comparison of kinematic and EMG parameters between unassisted, fixed- and adaptive-stiffness robotic-assisted ankle movements in post-stroke subjects
- Hybrid simulated annealing and genetic algorithm for optimization of a rule-based algorithm for detection of gait events in impaired subjects
- Adaptive impedance control applied to robot-aided neuro-rehabilitation of the ankle
- Controle de impedância adaptativo aplicado à reabilitação robótica do tornozelo
- Robust markovian impedance control applied to a modular knee-exoskeleton
- Adaptive algorithm for gait segmentation using a single IMU in the thigh pocket
Informações sobre o DOI: 10.1109/JSEN.2019.2951923 (Fonte: oaDOI API)
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