Single element remote-PPG

Wenjin Wang (Corresponding author), A.C. den Brinker, Gerard de Haan

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Uittreksel

Camera-based remote photoplethysmography technology (remote-PPG) has shown great potential for contactless pulse-rate monitoring. However, remote-PPG systems typically analyze face images, which may restrict applications in view of privacy-preserving regulations such as the recently announced General Data Protection Regulation in the European Union. In this paper, we investigate the case of using single-element sensing as an input for remote-PPG extraction, which prohibits facial analysis and thus evades privacy issues. It also improves the efficiency of data storage and transmission. In contrast to known remote-PPG solutions using skin-selection techniques, the input signals in a single-element setup will contain a non-negligible degree of signal components associated with non-skin areas. Current remote-PPG extraction methods based on physiological and optical properties of skin reflections are therefore no longer valid. A new remote-PPG method, named Soft Signature based extraction (SoftSig), is proposed to deal with this situation by softening the dependence of pulse extraction on prior knowledge. A large scale experiment validates the concept of single-element remote-PPG monitoring and shows the improvement of SoftSig over general purpose solutions.
TaalEngels
Pagina's2032-2043
TijdschriftIEEE Transactions on Biomedical Engineering
Volume66
Nummer van het tijdschrift7
Vroegere onlinedatum20 nov 2018
DOI's
StatusGepubliceerd - 1 jul 2019

Vingerafdruk

Photoplethysmography
Skin
Data privacy
Monitoring
Optical properties
Cameras
Data storage equipment

Trefwoorden

    Citeer dit

    Wang, Wenjin ; den Brinker, A.C. ; de Haan, Gerard. / Single element remote-PPG. In: IEEE Transactions on Biomedical Engineering. 2019 ; Vol. 66, Nr. 7. blz. 2032-2043
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    title = "Single element remote-PPG",
    abstract = "Camera-based remote photoplethysmography technology (remote-PPG) has shown great potential for contactless pulse-rate monitoring. However, remote-PPG systems typically analyze face images, which may restrict applications in view of privacy-preserving regulations such as the recently announced General Data Protection Regulation in the European Union. In this paper, we investigate the case of using single-element sensing as an input for remote-PPG extraction, which prohibits facial analysis and thus evades privacy issues. It also improves the efficiency of data storage and transmission. In contrast to known remote-PPG solutions using skin-selection techniques, the input signals in a single-element setup will contain a non-negligible degree of signal components associated with non-skin areas. Current remote-PPG extraction methods based on physiological and optical properties of skin reflections are therefore no longer valid. A new remote-PPG method, named Soft Signature based extraction (SoftSig), is proposed to deal with this situation by softening the dependence of pulse extraction on prior knowledge. A large scale experiment validates the concept of single-element remote-PPG monitoring and shows the improvement of SoftSig over general purpose solutions.",
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    Single element remote-PPG. / Wang, Wenjin (Corresponding author); den Brinker, A.C.; de Haan, Gerard.

    In: IEEE Transactions on Biomedical Engineering, Vol. 66, Nr. 7, 01.07.2019, blz. 2032-2043.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

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    N2 - Camera-based remote photoplethysmography technology (remote-PPG) has shown great potential for contactless pulse-rate monitoring. However, remote-PPG systems typically analyze face images, which may restrict applications in view of privacy-preserving regulations such as the recently announced General Data Protection Regulation in the European Union. In this paper, we investigate the case of using single-element sensing as an input for remote-PPG extraction, which prohibits facial analysis and thus evades privacy issues. It also improves the efficiency of data storage and transmission. In contrast to known remote-PPG solutions using skin-selection techniques, the input signals in a single-element setup will contain a non-negligible degree of signal components associated with non-skin areas. Current remote-PPG extraction methods based on physiological and optical properties of skin reflections are therefore no longer valid. A new remote-PPG method, named Soft Signature based extraction (SoftSig), is proposed to deal with this situation by softening the dependence of pulse extraction on prior knowledge. A large scale experiment validates the concept of single-element remote-PPG monitoring and shows the improvement of SoftSig over general purpose solutions.

    AB - Camera-based remote photoplethysmography technology (remote-PPG) has shown great potential for contactless pulse-rate monitoring. However, remote-PPG systems typically analyze face images, which may restrict applications in view of privacy-preserving regulations such as the recently announced General Data Protection Regulation in the European Union. In this paper, we investigate the case of using single-element sensing as an input for remote-PPG extraction, which prohibits facial analysis and thus evades privacy issues. It also improves the efficiency of data storage and transmission. In contrast to known remote-PPG solutions using skin-selection techniques, the input signals in a single-element setup will contain a non-negligible degree of signal components associated with non-skin areas. Current remote-PPG extraction methods based on physiological and optical properties of skin reflections are therefore no longer valid. A new remote-PPG method, named Soft Signature based extraction (SoftSig), is proposed to deal with this situation by softening the dependence of pulse extraction on prior knowledge. A large scale experiment validates the concept of single-element remote-PPG monitoring and shows the improvement of SoftSig over general purpose solutions.

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    Wang W, den Brinker AC, de Haan G. Single element remote-PPG. IEEE Transactions on Biomedical Engineering. 2019 jul 1;66(7):2032-2043. Beschikbaar vanaf, DOI: 10.1109/TBME.2018.2882396