Cargando…
Comparison of Decision Tree and Long Short-Term Memory Approaches for Automated Foot Strike Detection in Lower Extremity Amputee Populations
Foot strike detection is important when evaluating a person’s gait characteristics. Accelerometer and gyroscope signals from smartphones have been used to train artificial intelligence (AI) models for automated foot strike detection in able-bodied and elderly populations. However, there is limited r...
Autores principales: | Juneau, Pascale, Baddour, Natalie, Burger, Helena, Bavec, Andrej, Lemaire, Edward D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587033/ https://www.ncbi.nlm.nih.gov/pubmed/34770281 http://dx.doi.org/10.3390/s21216974 |
Ejemplares similares
-
Automated step detection with 6-minute walk test smartphone sensors signals for fall risk classification in lower limb amputees
por: Juneau, Pascale, et al.
Publicado: (2022) -
Amputee Fall Risk Classification Using Machine Learning and Smartphone Sensor Data from 2-Minute and 6-Minute Walk Tests
por: Juneau, Pascale, et al.
Publicado: (2022) -
Fall risk classification for people with lower extremity amputations using random forests and smartphone sensor features from a 6-minute walk test
por: Daines, Kyle J. F., et al.
Publicado: (2021) -
Quality of Life Experienced by Major Lower Extremity Amputees
por: Pran, Lemuel, et al.
Publicado: (2021) -
Postural Sway in Lower Extremity Amputees and Older Adults May Suggest Increased Fall Risk in Amputees
por: Bateni, H.
Publicado: (2020)