Abstract
AbstractPhotoplethysmography (PPG) offers a widely-used, convenient and non-invasive approach to monitoring basic indices of cardiovascular function such as heart rate and blood oxygenation. However, while the pulse waveform, generated by PPG comprises features that are shaped by physiological and psychological factors, it is frequently overlooked in analyses of such data. We suggest that studies could be enriched by exploiting the possibilities afforded by a systematic analysis of PPG waveforms. To do this we initially require a robust and automated means of characterising it, thereby allowing us to examine variations across individuals and between different physiological and psychological contexts. We present a psychophysiologically-relevant model, the Hybrid Excess and Decay (HED) Model, which characterises pulse wave morphology in terms of three underlying pressure waves and a decay function. We show that these parameters capture PPG data with a high degree of precision and, moreover, are sensitive to specific, physiologically-relevant changes within individuals. We present the theoretical and practical basis for the model and demonstrate its performance when applied to a pharmacological dataset of 105 participants receiving intravenous administrations of the sympathomimetic drug isoproterenol (Isoprenaline). We conclude by discussing the possible value in using the HED model to complement standard measures of PPG outputs.
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Edge Classification of Non-Invasive Blood Glucose Levels Based on Photoplethysmography Signals;2022 5th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI);2022-12-08