Evaluation of a PPG-based algorithm for prediction of neurally mediated syncope

摘要

Syncope is a transient and self-limited loss of consciousness that affects mostly elderly people. Although it is not lethal it can lead to serious injuries and the appearance of severe medical complications. With a high socioeconomic and medical impact, it is highly pertinent to develop personalized health systems that are capable of predicting impending syncope events and avoid major complications. In the later years we have been assisting to a rising interest on wearable monitoring systems and in several devices (e.g. sports watches) the photoplethysmogram (PPG) is already being used due to the easy applicability, cost effectiveness and unobtrusiveness. Thus, the development of an algorithm for syncope prediction that can be integrated on such systems would be of huge interest. In this paper we evaluate an algorithm for syncope prediction based on the analysis of the PPG signal alone and we compare it to our former algorithm based on the joint analysis of the electrocardiogram (ECG) and PPG signals.