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Trumpp, Alexander [VerfasserIn]; Lohr, Johannes [VerfasserIn]; Wedekind, Daniel [VerfasserIn]; Schmidt, Martin [VerfasserIn]; Burghardt, Matthias [VerfasserIn]; Heller, Axel R. [VerfasserIn]; Malberg, Hagen [VerfasserIn]; Zaunseder, Sebastian [VerfasserIn]

Camera-based photoplethysmography in an intraoperative setting

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  • Medientyp: E-Artikel
  • Titel: Camera-based photoplethysmography in an intraoperative setting
  • Beteiligte: Trumpp, Alexander [VerfasserIn]; Lohr, Johannes [VerfasserIn]; Wedekind, Daniel [VerfasserIn]; Schmidt, Martin [VerfasserIn]; Burghardt, Matthias [VerfasserIn]; Heller, Axel R. [VerfasserIn]; Malberg, Hagen [VerfasserIn]; Zaunseder, Sebastian [VerfasserIn]
  • Erschienen: London: BioMed Central, [2018]
  • Sprache: Englisch
  • DOI: 10.1186/s12938-018-0467-7
  • RVK-Notation: XA 10000 : Medizinische Zeitschriften
  • Schlagwörter: Level set methods ; Kamerabasierte Photoplethysmographie ; Intraoperative monitoring ; Camera-based photoplethysmography ; Intraoperatives Monitoring ; Fernüberwachung ; Publikationsfond ; Räumliche Homogenität ; Spatial homogeneity ; TU Dresden ; Publishing Fund ; Level Set Methoden ; Remote monitoring
  • Entstehung:
  • Anmerkungen: Quelle: Biomedical engineering online (2018), 17(1). ISSN: 1475-925X. DOI: 10.1186/s12938-018-0467-7. Artikelnr.: 33
  • Beschreibung: BackgroundCamera-based photoplethysmography (cbPPG) is a measurement technique which enables remote vital sign monitoring by using cameras. To obtain valid plethysmograms, proper regions of interest (ROIs) have to be selected in the video data. Most automated selection methods rely on specific spatial or temporal features limiting a broader application. In this work, we present a new method which overcomes those drawbacks and, therefore, allows cbPPG to be applied in an intraoperative environment.MethodsWe recorded 41 patients during surgery using an RGB and a near-infrared (NIR) camera. A Bayesian skin classifier was employed to detect suitable regions, and a level set segmentation approach to define and track ROIs based on spatial homogeneity.ResultsThe results show stable and homogeneously illuminated ROIs. We further evaluated their quality with regards to extracted cbPPG signals. The green channel provided the best results where heart rates could be correctly estimated in 95.6% of cases. The NIR channel yielded the highest contribution in compensating false estimations.ConclusionsThe proposed method proved that cbPPG is applicable in intraoperative environments. It can be easily transferred to other settings regardless of which body site is considered.
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung (CC BY)