Simulation for a Mems-Based CTRNN Ultra-Low Power Implementation of Human Activity Recognition

This paper presents an energy-efficient classification framework that performs human activity recognition (HAR). Typically, HAR classification tasks require a computational platform that includes a processor and memory along with sensors and their interfaces, all of which consume significant power....

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Detalles Bibliográficos
Autores principales: Emad-Ud-Din, Muhammad, Hasan, Mohammad H., Jafari, Roozbeh, Pourkamali, Siavash, Alsaleem, Fadi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Digital Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522023/
https://www.ncbi.nlm.nih.gov/pubmed/34713201
http://dx.doi.org/10.3389/fdgth.2021.731076

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8522023/
https://www.ncbi.nlm.nih.gov/pubmed/34713201
http://dx.doi.org/10.3389/fdgth.2021.731076

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