4.6 Article

Effects of Ballistocardiogram Peak Detection Jitters on the Quality of Heart Rate Variability Features: A Simulation-Based Case Study in the Context of Sleep Staging

Journal

SENSORS
Volume 23, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/s23052693

Keywords

ballistocardiogram; Bayes error; classifier; electrocardiogram; heartbeat interval; k-nearest neighbor; R-J interval; R-R interval; support vector machine

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Heart rate variability (HRV) features are important for clinical applications such as sleep staging. This study compares the use of ballistocardiograms (BCGs) and electrocardiograms (ECGs) for estimating HRV parameters and sleep staging, and finds that timing differences between BCGs and ECGs can affect the accuracy of sleep staging. The results suggest that BCG-based sleep staging can be comparable to ECG-based techniques, but there may be an increase in sleep-scoring error with larger timing differences.
Heart rate variability (HRV) features support several clinical applications, including sleep staging, and ballistocardiograms (BCGs) can be used to unobtrusively estimate these features. Electrocardiography is the traditional clinical standard for HRV estimation, but BCGs and electrocardiograms (ECGs) yield different estimates for heartbeat intervals (HBIs), leading to differences in calculated HRV parameters. This study examines the viability of using BCG-based HRV features for sleep staging by quantifying the impact of these timing differences on the resulting parameters of interest. We introduced a range of synthetic time offsets to simulate the differences between BCG- and ECG-based heartbeat intervals, and the resulting HRV features are used to perform sleep staging. Subsequently, we draw a relationship between the mean absolute error in HBIs and the resulting sleep-staging performances. We also extend our previous work in heartbeat interval identification algorithms to demonstrate that our simulated timing jitters are close representatives of errors between heartbeat interval measurements. This work indicates that BCG-based sleep staging can produce accuracies comparable to ECG-based techniques such that at an HBI error range of up to 60 ms, the sleep-scoring error could increase from 17% to 25% based on one of the scenarios we examined.

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