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Three methods for extracting respiratory rate from speckle plethysmography

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dc.contributor.authorHoogeveen, M. H.
dc.contributor.authorLorato, Ilde
dc.contributor.authorHerranz Olazabal, Jorge
dc.contributor.authorMorales Tellez, John
dc.contributor.authorHermeling, Evelien
dc.date.accessioned2026-03-19T14:59:13Z
dc.date.available2026-03-19T14:59:13Z
dc.date.createdwos2025-09-10
dc.date.issued2025
dc.description.abstractSpeckle plethysmography (SPG) is a novel technique for acquiring physiological data using laser speckle imaging. It is a promising signal modality for measuring vital signs both through contact and remote methods. Compared to photoplethysmography (PPG), SPG is more robust, being less sensitive to variations in ambient light and skin melanin content, while offering a superior signal-to-noise ratio. These attributes make SPG an attractive alternative for continuous monitoring in wearable or contact configurations. SPG has demonstrated reliability in extracting heart rate and heart rate variability, with results comparable to established gold standards. However, its application for respiratory rate (RR) detection remains unexplored. This study addresses this gap by extracting RR from SPG signals through the analysis of three key features: baseline wander, frequency modulation, and amplitude modulation. These techniques are commonly employed in the extraction of respiratory modulations from PPG signals. SPG data were collected using a contact sensor equipped with a near-infrared laser and a camera in reflective mode. Ten healthy volunteers participated in the study, placing their fingers on the SPG sensor. An algorithm was developed to extract RR by quantifying baseline, amplitude and frequency changes in the signals and was tested during phases of spontaneous and paced breathing. The extracted RR was compared to measurements obtained from respiratory belt signals, which were used as reference standard. During spontaneous breathing, for SPG a mean absolute error of 1.67 was observed with a Pearsons r of 0.68 for baseline wander of the peak as compared to the respiratory belt. Our results indicate that SPG effectively detects respiratory activity with accuracy comparable to the reference method. These results position SPG as an interesting modality for respiratory monitoring, further expanding its versatility in optical sensing applications.
dc.description.wosFundingTextPart of this research was funded by the National Growthfund PhotonDelta and the European Union's Horizon Europe research and innovation programme under grant agreement No 101115492, referred to as STIMULUS.
dc.identifier.doi10.1117/12.3041646
dc.identifier.isbn978-1-5106-8374-7
dc.identifier.issn1605-7422
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/58885
dc.language.isoeng
dc.provenance.editstepusergreet.vanhoof@imec.be
dc.publisherSPIE-INT SOC OPTICAL ENGINEERING
dc.source.beginpage133130B
dc.source.conferenceBiophotonics in Exercise Science, Sports Medicine, Health Monitoring Technologies, and Wearables VI
dc.source.conferencedate2025-01-25
dc.source.conferencelocationSan Francisco
dc.source.journalBIOPHOTONICS IN EXERCISE SCIENCE, SPORTS MEDICINE, HEALTH MONITORING TECHNOLOGIES, AND WEARABLES VI
dc.source.numberofpages8
dc.title

Three methods for extracting respiratory rate from speckle plethysmography

dc.typeProceedings paper
dspace.entity.typePublication
imec.identified.statusLibrary
imec.internal.crawledAt2025-10-22
imec.internal.sourcecrawler
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