Real-Time Cardiac Arrhythmia Classification Using TinyML on Ultra-Low-Cost Microcontrollers: A Feasibility Study for Resource-Constrained Environments.
Saved in:
| Title: | Real-Time Cardiac Arrhythmia Classification Using TinyML on Ultra-Low-Cost Microcontrollers: A Feasibility Study for Resource-Constrained Environments. |
|---|---|
| Authors: | Zambrano-de la Torre, Misael1 (AUTHOR), Guzman-Alfaro, Sebastian1,2 (AUTHOR) sebastian.guzman@uaz.edu.mx, Acuña-Correa, Andrea1,2 (AUTHOR), Soto-Murillo, Manuel A.1,2 (AUTHOR), Guzmán-Fernández, Maximiliano1 (AUTHOR), Robles-Ortiz, Ricardo1 (AUTHOR), Villagrana-Bañuelos, Karen E.1 (AUTHOR), Arceo-Olague, Jose G.1 (AUTHOR), Espino-Salinas, Carlos H.1 (AUTHOR), Sánchez-Reyna, Ana G.1 (AUTHOR), Cuevas-Rodriguez, Erik O.1 (AUTHOR) |
| Source: | Bioengineering (Basel). May2026, Vol. 13 Issue 5, p532. 26p. |
| Database: | Academic Search Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 23065354 |
|---|---|
| DOI: | 10.3390/bioengineering13050532 |
