Camera-based assessment of arterial stiffness and wave reflection parameters from neck micro-motion. (28th July 2017)

• Record Type: Journal Article
• Authors: Moço, A V; Mondragon, L Z; Wang, W; Stuijk, S; de Haan, G
• Is Part Of: Physiological measurement. Volume 38:Number 8(2017:Aug.)
• Page Start: 1576
• Page End: 1598
• Publication Date: 2017-07-28
• Subjects: cardiovascular health -- arterial stiffness -- carotid artery -- signal processing -- computer vision; Physiology -- Measurement -- Periodicals; Patient monitoring -- Periodicals; 612
• DOI: 10.1088/1361-6579/aa7d43
• Languages: English
• ISSNs: 0967-3334

Abstract

Abstract: The feasibility of a camera-based extraction of carotid distension waveforms offers the prospect of a user-friendly alternative to laser Doppler velocimetry (LDV) or accelerometry-based systems. Upon supplementary calibration of vessel wall displacement to arterial pressure, our system may also be an appealing alternative to applanation tonometry for extracting cardiac-related features from the central pulse pressure waveform. Objective : This paper describes the application of camera-based micro-motion imaging to extract health-related features from the contour of the carotid displacement waveform. Approach : We build on the assumption that the cardiac-related frequency components of the skin motion (sMOT) waveform, as acquired at the vicinity of the carotid artery under uneven illumination, receive a dominant contribution from the carotid wall displacement. We propose a two-step approach at which sMOT signals are queried based on the local amplitude of remote-photoplethysmography sensors spanning the neck's skin and then ensemble-averaged for cardiovascular health assessment. Main results : The feasibility of the system is demonstrated for assessing stiffness index, augmentation pressure, augmentation index and reflection magnitude on a dataset comprising 28 participants (ages 23 to 62 yrs; 22 males). Significance : Although presented here as a standalone system, micro-motion imaging can be an auxiliary technique for improving sensor placement and signal quality of tonometric or LDV technologies.