Performance analysis of remote photoplethysmography deep filtering using long short-term memory neural network

Performance analysis of remote photoplethysmography deep filtering using long short-term memory neural network

Abstract Background Remote photoplethysmography (rPPG) is a technique developed to estimate heart rate using standard video cameras and ambient light. Due to the multiple sources of noise that deteriorate the quality of the signal, conventional filters such as the bandpass and wavelet-based filters...

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Bibliographic Details
Main Authors: Deivid Botina-Monsalve, Yannick Benezeth, Johel Miteran
Format: Article
Language:English
Published: BMC 2022-09-01
Series:BioMedical Engineering OnLine
Subjects:
Remote photoplethysmography
rPPG filtering
Signal enhancement
Long short-term memory
MMSE-HR
VIPL-HR
Online Access:https://doi.org/10.1186/s12938-022-01037-z

Internet

https://doi.org/10.1186/s12938-022-01037-z

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