Device for ECG prediction based on retinal vasculature analysis

TL;DR

This paper presents a portable, automated device that captures retinal images and analyzes pulsatile vessel changes to predict ECG and systemic vascular diseases non-invasively.

Contribution

The work introduces a novel handheld device that automatically analyzes retinal vessel pulsations for cardiovascular and systemic disease assessment.

Findings

Device successfully captures retinal vessel diameter variations.

Automated analysis correlates retinal pulsations with ECG signals.

Potential for non-invasive diagnosis of vascular diseases.

Abstract

Pulsatile changes in retinal vascular geometry over the cardiac cycle have clinical implications for the diagnosis of ocular and systemic vascular diseases, including ischemia, coronary heart diseases, and diabetes mellitus and its complications. Thus, analysis of the pulsatile changes over the cardiac cycle is a potential non-invasive assessment for the presence of ocular and systemic vascular diseases. The cardiac rhythm influences these pulsatile changes in the retina, is a result of the change in blood volumetric flow entering the ophthalmic-vascular system under a certain level of intraocular pressure during the peak systolic and diastolic phases of the cardiac cycle. Assessment of fundus images generally requires ophthalmologic expertise. However, the availability of an expert is not always guaranteed, and even if an expert is available, the assessment is performed manually. Thus, there is also a need for an automated device that can analyze the fundus images and keep track of the pulsations. Such a device can be synchronized with the Electrocardiogram and can be programmed to assess the presence of various ocular and systemic vascular diseases. In this project, we proposed and worked on a portable embedded system device that automatically captures retinal images and analyzes them for the estimation of vessel diameters. The device is hand-held and attaches to the ophthalmoscope as an extension. Using the device, the time variation of the vessel diameters can be estimated, which can further be used to predict ECG and the presence of various other systemic vascular diseases.