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On the potential of AI based health assessment from photopletysmographic signals
1 : Laboratoire Analyse, Géométrie et Applications
Université Paris 8 Vincennes-Saint-Denis, Centre National de la Recherche Scientifique, Université Sorbonne Paris nord
2 : ARMEDIA
Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux
3 : Clinique Bizet
Clinique Bizet
4 : Université Sorbonne Paris Nord - UFR des Sciences de la communication
Université Sorbonne Paris nord
The necessity of implementing new options to improve telemedicine has gained much importance in recent years. Among all the available technologies, photoplethysmography is turning out to be a promising resource. Its cost effectiveness and its usability allow its embedding in several devices without the need of constraining requirements. In this paper, we explore how artificial intelligence-based approaches could improve the photoplethysmography use by leveraging its potential and minimizing its disadvantages.
