Cargando…
Automatically evaluating balance using machine learning and data from a single inertial measurement unit
BACKGROUND: Recently, machine learning techniques have been applied to data collected from inertial measurement units to automatically assess balance, but rely on hand-engineered features. We explore the utility of machine learning to automatically extract important features from inertial measuremen...
Autores principales: | Kamran, Fahad, Harrold, Kathryn, Zwier, Jonathan, Carender, Wendy, Bao, Tian, Sienko, Kathleen H., Wiens, Jenna |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278701/ https://www.ncbi.nlm.nih.gov/pubmed/34256799 http://dx.doi.org/10.1186/s12984-021-00894-4 |
Ejemplares similares
-
Automatic ML-based vestibular gait classification: examining the effects of IMU placement and gait task selection
por: Jabri, Safa, et al.
Publicado: (2022) -
Differences between physical therapist ratings, self-ratings, and posturographic measures when assessing static balance exercise intensity
por: Ferris, Jamie, et al.
Publicado: (2023) -
The effects of attractive vs. repulsive instructional cuing on balance performance
por: Kinnaird, Catherine, et al.
Publicado: (2016) -
Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units
por: Hauth, Jeremiah, et al.
Publicado: (2021) -
Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept
por: Xu, Junkai, et al.
Publicado: (2017)