Contact-Free Pulse Signal Extraction from Human Face Videos: A Review and New Optimized Filtering Approach

Muhammad Waqar, Reyer Zwiggelaar, Bernard Tiddeman*

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddPennod

1 Dyfyniad (Scopus)

Crynodeb

In this chapter, we review methods for video-based heart monitoring, from classical signal processing approaches to modern deep learning methods. In addition, we propose a new method for learning an optimal filter that can overcome many of the problems that can affect classical approaches, such as light reflection and subject’s movements, at a fraction of the training cost of deep learning approaches. Following the usual procedures for region of interest extraction and tracking, robust skin color estimation and signal pre-processing, we introduce a least-squares error optimal filter, learnt using an established training dataset to estimate the photoplethysmographic (PPG) signal more accurately from the measured color changes over time. This method not only improves the accuracy of heart rate measurement but also resulted in the extraction of a cleaner pulse signal, which could be integrated into many other useful applications such as human biometric recognition or recognition of emotional state. The method was tested on the DEAP dataset and showed improved performance over the best previous classical method on that dataset. The results obtained show that our proposed contact-free heart rate measurement method has significantly improved on existing methods.

Iaith wreiddiolSaesneg
TeitlAdvances in Experimental Medicine and Biology
GolygyddionPaul M. Rea
CyhoeddwrSpringer Nature
Pennod10
Tudalennau181-202
Nifer y tudalennau22
Cyfrol9
Argraffiad1
ISBN (Electronig)9783030611255
ISBN (Argraffiad)9783030611248, 9783030611279
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 2021

Cyfres gyhoeddiadau

EnwAdvances in Experimental Medicine and Biology
Cyfrol1317
ISSN (Argraffiad)0065-2598
ISSN (Electronig)2214-8019

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