Tiny-HR: Towards an interpretable machine learning pipeline for heart rate estimation on edge devices

The focus of this paper is a proof of concept, machine learning (ML) pipeline that extracts heart rate from pressure sensor data acquired on low-power edge devices. The ML pipeline consists an upsampler neural network, a signal quality classifier, and a 1D-convolutional neural network optimized for...

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Bibliographische Detailangaben

Hauptverfasser:	Anbukarasu, Preetam, Nanisetty, Shailesh, Tata, Ganesh, Ray, Nilanjan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Human-Computer Interaction Computer Science - Learning
Online-Zugang:	Volltext bestellen
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