Machine learning applied to reference signal-less detection of motion artifacts in photoplethysmographic signals: A review

Machine learning algorithms have brought remarkable advancements in detecting motion artifacts (MAs) from the photoplethysmogram (PPG) with no measured or synthetic reference data. However, no study has provided a synthesis of these methods, let alone an in-depth discussion to aid in deciding which...

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Autores:
Castillo García, Javier Ferney
Argüello-Prada, Erick Javier
Tipo de recurso:
Article of investigation
Fecha de publicación:
2024
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
eng
OAI Identifier:
oai:red.uao.edu.co:10614/16262
Acceso en línea:
https://hdl.handle.net/10614/16262
https://red.uao.edu.co/
Palabra clave:
Motion artifacts
Photoplethysmogram
Machine learning
Reference signal-less methods
Real-time applications
Computational complexity
Artefactos de movimiento
Fotopletismograma
Aprendizaje automático
Métodos sin señal de referencia
Aplicaciones en tiempo real
Complejidad computacional
Rights
openAccess
License
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