Cardiac-gated slit lamp videography as a novel approach to assessing a microcirculatory network

Paul F. Brennan, Dewar D. Finlay, Mark S. Spence, Agnes Awauh, James A.D. McLaughlin, Jonathan E. Moore, M. Andrew Nesbit, Emanuele Trucco, Ruixuan Wang, C. B. Tara Moore

Research output: Contribution to journalArticle

Abstract

In this article we describe the development of a system that is designed to image and in turn, allow characterization of the microcirculation in conjunctiva. To characterise the blood flow the system simultaneously captures high quality imagery alongside information on the cardiac cycle, using a multimodal image and biosignal acquisition approach. Images are captured using a smartphone camera attached, via a bespoke adapter, to a 40x magnification slit lamp. Images are recorded as videos at a resolution of up to approximately 1920 x 1080 pixels per frame (i.e. 1080k) and sampled at 60 frames per second. Information on the cardiac cycle is captured using a phonocardiogram device. In order to allow time synchronisation of the video with the phonocardiogram, the phonocardiogram output signal is fed via a custom adapter to the audio input of the smartphone video recording device. This allows for the phonocardiogram to be time synchronised in the audio layer of the video file. This software system provides the opportunity for cardiac gated assessment of a readily obtainable microvascular network, namely the conjunctival vasculature.

Original languageEnglish
Pages (from-to)1-4
Number of pages4
JournalComputing in Cardiology
Volume44
DOIs
Publication statusPublished - 2017

Fingerprint Dive into the research topics of 'Cardiac-gated slit lamp videography as a novel approach to assessing a microcirculatory network'. Together they form a unique fingerprint.

  • Cite this

    Brennan, P. F., Finlay, D. D., Spence, M. S., Awauh, A., McLaughlin, J. A. D., Moore, J. E., Nesbit, M. A., Trucco, E., Wang, R., & Moore, C. B. T. (2017). Cardiac-gated slit lamp videography as a novel approach to assessing a microcirculatory network. Computing in Cardiology, 44, 1-4. https://doi.org/10.22489/CinC.2017.138-248