Cargando…
Classification of gait phases based on a machine learning approach using muscle synergy
The accurate detection of the gait phase is crucial for monitoring and diagnosing neurological and musculoskeletal disorders and for the precise control of lower limb assistive devices. In studying locomotion mode identification and rehabilitation of neurological disorders, the concept of modular or...
Autores principales: | Park, Heesu, Han, Sungmin, Sung, Joohwan, Hwang, Soree, Youn, Inchan, Kim, Seung-Jong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230056/ https://www.ncbi.nlm.nih.gov/pubmed/37266322 http://dx.doi.org/10.3389/fnhum.2023.1201935 |
Ejemplares similares
-
Prediction of Lower Extremity Multi-Joint Angles during Overground Walking by Using a Single IMU with a Low Frequency Based on an LSTM Recurrent Neural Network
por: Sung, Joohwan, et al.
Publicado: (2021) -
Identification of muscle synergies associated with gait transition in humans
por: Hagio, Shota, et al.
Publicado: (2015) -
Do Muscle Synergies Improve Optimization Prediction of Muscle Activations During Gait?
por: Michaud, Florian, et al.
Publicado: (2020) -
Muscle synergy space: learning model to create an optimal muscle synergy
por: Alnajjar, Fady, et al.
Publicado: (2013) -
The flexion synergy, mother of all synergies and father of new models of gait
por: Duysens, Jacques, et al.
Publicado: (2013)