ArticlePeerJ2018
A wavelet-based decomposition method for a robust extraction of pulse rate from video recordings.
Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement.Frontiers in bioengineering and biotechnology · 2024Review
- Heart Rate Estimation from Facial Image Sequences of a Dual-Modality RGB-NIR Camera.Sensors (Basel, Switzerland) · 2023Article
- Optic chiasmatic potential by endoscopically implanted skull base microinvasive biosensor: a brain-machine interface approach for anterior visual pathway assessment.Theranostics · 2022Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRemote photoplethysmography (rPPG) is a promising optical method for non-contact assessment of pulse rate (PR) from video recordings. In order to implement the method in real-time applications, it is necessary for the rPPG algorithms to be capable of eliminating as many distortions from the pulse signal as possible.
methodsIn order to increase the degrees-of-freedom of the distortion elimination, the dimensionality of the RGB video signals is increased by the wavelet transform decomposition using the generalized Morse wavelet. The proposed Continuous-Wavelet-Transform-based Sub-Band rPPG method (SB-CWT) is evaluated on the 101 publicly available RGB facial video recordings and corresponding reference blood volume pulse (BVP) signals taken from the MMSE-HR database. The performance of the SB-CWT is compared with the performance of the state-of-the-art Sub-band rPPG (SB).
resultsMedian signal-to-noise ratio (SNR) for the proposed SB-CWT ranges from 6.63 to 10.39 dB and for the SB from 4.23 to 6.24 dB. The agreement between the estimated PRs from rPPG pulse signals and the reference signals in terms of the coefficients of determination ranges from 0.81 to 0.91 for SB-CWT and from 0.41 to 0.47 for SB. All the correlation coefficients are statistically significant ( DISCUSSION: The results show that the proposed SB-CWT outperforms SB in terms of SNR and the agreement between the estimated PRs from RGB video signals and PRs from the reference BVP signals.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.