Cargando…
Fall Detection Using Multiple Bioradars and Convolutional Neural Networks
A lack of effective non-contact methods for automatic fall detection, which may result in the development of health and life-threatening conditions, is a great problem of modern medicine, and in particular, geriatrics. The purpose of the present work was to investigate the advantages of utilizing a...
Autores principales: | Anishchenko, Lesya, Zhuravlev, Andrey, Chizh, Margarita |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960824/ https://www.ncbi.nlm.nih.gov/pubmed/31861061 http://dx.doi.org/10.3390/s19245569 |
Ejemplares similares
-
Contactless Fall Detection by Means of Multiple Bioradars and Transfer Learning
por: Lobanova, Vera, et al.
Publicado: (2022) -
Challenges and Potential Solutions of Psychophysiological State Monitoring with Bioradar Technology
por: Anishchenko, Lesya
Publicado: (2018) -
Accelerometer-Based Human Fall Detection Using Convolutional Neural Networks
por: Santos, Guto Leoni, et al.
Publicado: (2019) -
Frequency Comb-Based Ground-Penetrating Bioradar: System Implementation and Signal Processing
por: Shi, Di, et al.
Publicado: (2023) -
A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets
por: Casilari, Eduardo, et al.
Publicado: (2020)