Deep Learning Approach for Extracting Heart Rate Variability from a Photoplethysmographic Signal

Deep Learning Approach for Extracting Heart Rate Variability from a Photoplethysmographic Signal

Photoplethysmography (PPG) is a method to detect blood volume changes in every heartbeat. The peaks in the PPG signal corresponds to the electrical impulses sent by the heart. The duration between each heartbeat varies, and these variances are better known as heart rate variability (HRV). Thus, find...

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Bibliographic Details
Main Authors:	Odinsdottir, Gudny Björk, Larsson, Jesper
Format:	Others
Language:	English
Published:	Högskolan Kristianstad, Fakulteten för naturvetenskap 2020
Subjects:	Heart rate variability photoplethysmograpic signal human activity recognition deep learning approach recurrent neural network long short-term memory network Computer Sciences Datavetenskap (datalogi)
Online Access:	http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-21368

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