Which wavelength is the best for arterial pulse waveform extraction using laser speckle imaging?

Pedro Vaz, Tânia Pereira, Edite Figueiras, Carlos Correia, Anne Humeau-Heurtier, João Cardoso

    Research output: Contribution to journalArticleScientificpeer-review

    13 Citations (Scopus)

    Abstract

    A multi-wavelengths analysis for pulse waveform extraction using laser speckle is conducted. The proposed system consists of three coherent light sources (532 nm, 635 nm, 850 nm). A bench-test composed of a moving skin-like phantom (silicone membrane) is used to compare the results obtained from different wavelengths. The system is able to identify a skin-like phantom vibration frequency, within physiological values, with a minimum error of 0.5 mHz for the 635 nm and 850 nm wavelengths and a minimum error of 1.3 mHz for the 532 nm light wavelength using a FFT-based algorithm. The phantom velocity profile is estimated with an error ranging from 27% to 9% using a bidimensional correlation coefficient-based algorithm. An in vivo trial is also conducted, using the 532 nm and 635 nm laser sources. The 850 nm light source has not been able to extract the pulse waveform. The heart rate is identified with a minimum error of 0.48 beats per minute for the 532 nm light source and a minimal error of 1.15 beats per minute for the 635 nm light source. Our work reveals that a laser speckle-based system with a 532 nm wavelength is able to give arterial pulse waveform with better results than those given with a 635 nm laser.

    Original languageEnglish
    Pages (from-to)188-195
    Number of pages8
    JournalBiomedical Signal Processing and Control
    Volume25
    DOIs
    Publication statusPublished - Mar 2016
    Publication typeA1 Journal article-refereed

    Keywords

    • Arterial pulse waveform
    • Correlation
    • Fast Fourier transform
    • Laser speckle
    • Multi-spectral

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Health Informatics
    • Signal Processing

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