title: Cardiorespiratory interactions: Noncontact assessment using laser Doppler vibrometry.
abstract: The application of a noncontact physiological recording technique, based on the method of laser Doppler vibrometry (LDV), is described. The effectiveness of the LDV method as a physiological recording modality lies in the ability to detect very small movements of the skin, associated with internal mechanophysiological activities. The method is validated for a range of cardiovascular variables, extracted from the contour of the carotid pulse waveform as a function of phase of the respiration cycle. Data were obtained from 32 young healthy participants, while resting and breathing spontaneously. Individual beats were assigned to four segments, corresponding with inspiration and expiration peaks and transitional periods. Measures relating to cardiac and vascular dynamics are shown to agree with the pattern of effects seen in the substantial body of literature based on human and animal experiments, and with selected signals recorded simultaneously with conventional sensors. These effects include changes in heart rate, systolic time intervals, and stroke volume. There was also some evidence for vascular adjustments over the respiration cycle. The effectiveness of custom algorithmic approaches for extracting the key signal features was confirmed. The advantages of the LDV method are discussed in terms of the metrological properties and utility in psychophysiological research. Although used here within a suite of conventional sensors and electrodes, the LDV method can be used on a stand-alone, noncontact basis, with no requirement for skin preparation, and can be used in harsh environments including the MR scanner.
authors.affiliation: Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA.
authors.forename: Erik J
authors.initials: EJ
authors.lastname: Sirevaag
authors.affiliation: Preston M. Green Department of Electrical and Systems Engineering, School of Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.|Department of Industrial Engineering and Mathematical Science, Università Politecnica delle Marche, Ancona, Italy.
authors.forename: Sara
authors.initials: S
authors.lastname: Casaccia
authors.affiliation: Preston M. Green Department of Electrical and Systems Engineering, School of Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.
authors.forename: Edward A
authors.initials: EA
authors.lastname: Richter
authors.affiliation: Preston M. Green Department of Electrical and Systems Engineering, School of Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: O'Sullivan
authors.affiliation: Department of Industrial Engineering and Mathematical Science, Università Politecnica delle Marche, Ancona, Italy.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Scalise
authors.affiliation: Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA.
authors.forename: John W
authors.initials: JW
authors.lastname: Rohrbaugh
mesh_terms: D000328:Adult; D004301:Doppler Effect; D022062:Electrophysiologic Techniques, Cardiac / Q000379:methods*; D005260:Female; D006339:Heart Rate; D006801:Humans; D008297:Male; D012119:Respiration; D012815:Signal Processing, Computer-Assisted; D014732:Vibration; D055815:Young Adult
keywords: Autonomic; Cardiovascular; Other; Respiration