Identification of gait events in healthy subjects and with parkinson’s disease using inertial sensors: an adaptive unsupervised learning approach (2020)
- Authors:
- USP affiliated authors: SIQUEIRA, ADRIANO ALMEIDA GONÇALVES - EESC ; IBARRA, JUAN CARLOS PEREZ - EESC
- Unidade: EESC
- DOI: 10.1109/TNSRE.2020.3039999
- Subjects: DOENÇA DE PARKINSON; ROBÓTICA; PROCESSOS DE MARKOV; BIOMECÂNICA; ENGENHARIA MECÂNICA
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ, USA
- Date published: 2020
- Source:
- Título: IEEE Transactions on Neural Systems and Rehabilitation Engineering
- ISSN: 1534-4320
- Volume/Número/Paginação/Ano: v. 28, n. 12, p. 2933-2943, 2020
- Status:
- Artigo possui versão em acesso aberto em repositório (Green Open Access)
- Versão do Documento:
- Versão submetida (Pré-print)
- Acessar versão aberta:
-
ABNT
PÉREZ IBARRA, Juan Carlos e SIQUEIRA, Adriano Almeida Gonçalves e KREBS, Hermano Igo. Identification of gait events in healthy subjects and with parkinson’s disease using inertial sensors: an adaptive unsupervised learning approach. IEEE Transactions on Neural Systems and Rehabilitation Engineering, v. 28, n. 12, p. 2933-2943, 2020Tradução . . Disponível em: https://doi.org/10.1109/TNSRE.2020.3039999. Acesso em: 08 abr. 2026. -
APA
Pérez Ibarra, J. C., Siqueira, A. A. G., & Krebs, H. I. (2020). Identification of gait events in healthy subjects and with parkinson’s disease using inertial sensors: an adaptive unsupervised learning approach. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28( 12), 2933-2943. doi:10.1109/TNSRE.2020.3039999 -
NLM
Pérez Ibarra JC, Siqueira AAG, Krebs HI. Identification of gait events in healthy subjects and with parkinson’s disease using inertial sensors: an adaptive unsupervised learning approach [Internet]. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2020 ; 28( 12): 2933-2943.[citado 2026 abr. 08 ] Available from: https://doi.org/10.1109/TNSRE.2020.3039999 -
Vancouver
Pérez Ibarra JC, Siqueira AAG, Krebs HI. Identification of gait events in healthy subjects and with parkinson’s disease using inertial sensors: an adaptive unsupervised learning approach [Internet]. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2020 ; 28( 12): 2933-2943.[citado 2026 abr. 08 ] Available from: https://doi.org/10.1109/TNSRE.2020.3039999 - Real-time identification of impaired gait phases using a single foot-mounted inertial sensor: review and feasibility study
- Comparison of kinematic and EMG parameters between unassisted, fixed- and adaptive-stiffness robotic-assisted ankle movements in post-stroke subjects
- Real-time identification of gait events in impaired subjects using a single-IMU foot-mounted device
- 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
- 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 a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Por se tratar de integração com serviço externo, podem existir diferentes versões do trabalho (como preprints ou postprints), que podem diferir da versão publicada.
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
Identification_of_Gait_Ev... |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
