Greedy-optimized Approach for Interbeat Interval and Heart Rate Variability Daily Monitoring using Wearable PPG
Luffina C. Huang

TL;DR
This paper introduces a greedy-optimized method for accurately estimating interbeat intervals and heart rate variability from wearable PPG signals during daily activities, effectively reducing motion artifacts.
Contribution
A novel greedy-optimized shortest path approach for IBI estimation from PPG signals, improving accuracy during intensive daily activities.
Findings
Achieved 0.96 correlation in IBI estimation from single-channel PPG.
Reduced percentage error by 58.4% compared to previous methods.
Validated robustness on the PPG-DaLiA dataset across daily activities.
Abstract
Continuous monitoring of heart rate variability (HRV) provides insights in cardiovascular health. Wearable Photoplethysmography (PPG) assures convenient measurement of HRV. PPG, however, is susceptible to motion artifacts, considerably deteriorating the accuracy in estimation. In this study, a greedy-optimized approach is proposed for attaining high accuracy of interbeat intervals (IBIs) estimation from PPG signals collected during intensive daily activities. Utilizing the fact of continuity in heartbeats, the IBI estimation is converted into the shortest path problem in a directed acyclic graph, where candidate heartbeats from motion-contaminated PPG are regarded as vertices. The approach exploits a convex penalty function to optimize weight assignment in the shortest path calculation and a greedy fusion method to strengthen the selection process of optimal IBIs. Results achieve…
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Taxonomy
TopicsNon-Invasive Vital Sign Monitoring · Heart Rate Variability and Autonomic Control · ECG Monitoring and Analysis
