Statistical Analysis of the Reliability of Data Collected with Wireless Electrocardiograms Outside Clinical Settings

TL;DR

This study evaluates the reliability of wireless ECG data collected outside clinical settings by comparing it with standard clinical ECG data, finding significant statistical agreement in heart rate variability measures.

Contribution

It provides a comprehensive statistical analysis demonstrating the reliability of wireless ECGs for long-term cardiac monitoring outside clinics.

Findings

Wireless ECG data shows significant agreement with clinical ECG data.

95% confidence intervals support the reliability of wireless ECG measurements.

No significant statistical difference found between datasets for RR intervals and HRV.

Abstract

Cost-effective wireless electrocardiograms (ECGs) enable long-term and scalable monitoring of cardiac patients in their home and work environments. Because they offer greater freedom of movement, they are also suitable for investigating the relationship between cardiac workload and underlying physical exertion. However, this requires that the quality of the generated data meets the standards of clinical devices. The aim of this study is to examine this closely. We therefore analyze data from 54 healthy subjects who performed five physical activities using wireless ECGs outside of clinical settings and without medical supervision. The results are compared with clinically collected data from standard 12-lead ECGs (2493 subjects) and Holter ECGs (29 subjects), with particular attention to the RR interval time series (tachogram) and heart rate variability (HRV). Our study shows significant statistical agreement between the different datasets. We calculated the 95% confidence intervals for the mean RR interval and HRV assuming that (1) the statistics of the 12-lead ECGs could serve as reliable reference, and (2) the statistics of the 12-lead ECGs cannot be taken as reliable reference. The p-values for both conditions (for the RR interval: 0.23 and 0.26 respectively; for HRV: 0.10 and 0.11 respectively) suggest that there is insufficient evidence to reject the hypothesis that significant statistical agreement exists between the different datasets.