- AutorIn
- Daniel Wedekind Institute of Biomedical Engineering, Technische Universität Dresden
- Alexander TrumppInstitute of Biomedical Engineering, Technische Universität Dresden
- Frederik GaetjenUniversity Hospital Carl Gustav Carus Dresden, Herzzentrum Dresdem GmbH, Technische Universität Dresden
- Stefan Rasche
- Klaus Matschke
- Hagen Malberg
- Sebastian Zaunseder
- Titel
- Assessment of blind source separation techniques for video-based cardiac pulse extraction
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-352679
- Quellenangabe
- Journal of Biomedical Optics Herausgeber: Brian W. Pogue
Erscheinungsort: Bellingham, Wash.
Verlag: SPIE
Erscheinungsjahr: 2017
Jahrgang: 22
Heft: 3
Seiten: 035002-1-035002-14
ISSN: 1560-2281 - Erstveröffentlichung
- 2017
- Abstract (EN)
- Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of BSS and its general benefit. This contribution investigates the performance of BSS to enhance the cardiac pulse from cbPPGs in dependency to varying input data characteristics. The BSS input conditions are controlled by an automated spatial preselection routine of regions of interest. Input data of different characteristics (wavelength, dominant frequency, and signal quality) from 18 postoperative cardiovascular patients are processed with standard BSS techniques, namely principal component analysis (PCA) and independent component analysis (ICA). The effect of BSS is assessed by the spectral signal-tonoise ratio (SNR) of the cardiac pulse. The preselection of cbPPGs, appears beneficial providing higher SNR compared to standard cbPPGs. Both, PCA and ICA yielded better outcomes by using monochrome inputs (green wavelength) instead of inputs of different wavelengths. PCA outperforms ICA for more homogeneous input signals. Moreover, for high input SNR, the application of ICA using standard contrast is likely to decrease the SNR.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der Zeitschrift Journal of Biomedical Optics' erschienen ist.
DOI: 10.1117/1.JBO.22.3.035002 - Freie Schlagwörter (DE)
- blinde Quellentrennung, unabhängige Komponentenanalyse, Hauptkomponentenanalyse, videobasierte Überwachung der Vitalfunktionen, kamerabasiertes Fotoplethysmogramm, Signal-Rausch-Verhältnis
- Freie Schlagwörter (EN)
- blind source separation, independent component analysis, principal component analysis, video-based vital signs monitoring, camera-based photoplethysmogram, signal-to-noise ratio
- Klassifikation (DDC)
- 530, 610
- Verlag
- SPIE, Bellingham, Wash.
- Förder- / Projektangaben
- Sächsisches Staatsministerium für Wissenschaft und Kunst CardioVisio
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-352679
- Veröffentlichungsdatum Qucosa
- 09.09.2019
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis