Extracting heart rate variability from nirs signals for an explainable detection of learning disorders
Artificial Intelligence (AI) has improved our ability to process large amounts of data. These tools are particularly interesting in medical contexts because they evaluate the variables from patients’ screening evaluation and disentangle the information that they contain. In this study, we propose a...
- Autores:
-
Arco, Juan E.
Gallego-Molina, Nicolás J.
López-Pérez, Pedro J.
Ramírez, Javier
Górriz, Juan M.
Ortiz, Andrés
- Tipo de recurso:
- Part of book
- Fecha de publicación:
- 2024
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/13820
- Acceso en línea:
- https://hdl.handle.net/11323/13820
https://repositorio.cuc.edu.co/
- Palabra clave:
- Dyslexia
Explicability
Heart rate variability
Machine learning
NIRS
Signal processing
- Rights
- closedAccess
- License
- Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)