Cargando…
Human Activity Recognition Based on Symbolic Representation Algorithms for Inertial Sensors
Mobile sensing has allowed the emergence of a variety of solutions related to the monitoring and recognition of human activities (HAR). Such solutions have been implemented in smartphones for the purpose of better understanding human behavior. However, such solutions still suffer from the limitation...
Autores principales: | Sousa Lima, Wesllen, de Souza Bragança, Hendrio L., Montero Quispe, Kevin G., Pereira Souto, Eduardo J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263747/ https://www.ncbi.nlm.nih.gov/pubmed/30463336 http://dx.doi.org/10.3390/s18114045 |
Ejemplares similares
-
MBOSS: A Symbolic Representation of Human Activity Recognition Using Mobile Sensors
por: Montero Quispe, Kevin G., et al.
Publicado: (2018) -
A Smartphone Lightweight Method for Human Activity Recognition Based on Information Theory
por: Bragança, Hendrio, et al.
Publicado: (2020) -
Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview
por: Sousa Lima, Wesllen, et al.
Publicado: (2019) -
How Validation Methodology Influences Human Activity Recognition Mobile Systems
por: Bragança, Hendrio, et al.
Publicado: (2022) -
Applying Self-Supervised Representation Learning for Emotion Recognition Using Physiological Signals
por: Montero Quispe, Kevin G., et al.
Publicado: (2022)