In plain language
Heart rate variability (HRV) — the small beat-to-beat changes in the timing of the heartbeat — is a widely used marker of stress, emotion regulation, and cardiac health. Traditionally it is measured with a wired electrocardiogram (ECG) in a lab, but wristband devices that use light-based sensors (photoplethysmography, or PPG) promise to measure HRV comfortably and cheaply in everyday life. The question this study asks is simple but important: can you trust the data these wristbands produce?
The researchers put Empatica's E4, a high-end research wristband, to the test against a wired ECG in 78 undergraduates. Participants were measured across a range of conditions — sitting, lying down, and standing at rest, plus a typing task and a grip-strength task — so the device could be evaluated during both stillness and movement. Crucially, the authors also introduce a new method for estimating how much error is present in each recording and for setting a tolerance threshold to discard corrupted data.
The results are a caution to researchers. The E4 was severely compromised by motion: outside of sitting and lying still, a large share of the heartbeat data was missing or unusable. When the participant held still, the wristband agreed reasonably well with the ECG, and applying the error-tolerance method pushed agreement very high — but only by throwing away a large fraction of participants. The paper concludes that PPG wristbands should be used with caution for HRV, and offers a simple, adaptable error-detection technique that any researcher can apply to check their data quality.
Key findings
- The Empatica E4 wristband was compared against wired ECG in 78 undergraduates across seated, supine, and standing baselines plus typing and grip-strength tasks.
- The E4 was severely compromised by motion artifact, producing a high percentage of missing data in every condition except seated and supine rest.
- During still conditions, frequency-based HRV measures from the E4 and ECG correlated moderately to strongly (.40 to .82); applying stricter error cutoffs raised correlations to as high as .97–.98 but roughly halved the usable sample.
- When participants were standing, typing, or gripping, filtering to under 25% missing heartbeats left 15 or fewer viable cases — too few for reliable HRV estimates; typing data were almost entirely rejected.
- The paper's key contribution is a new, simple-to-implement method for estimating error in PPG-based HRV data and setting adjustable error-tolerance cutoffs.
- The authors recommend caution when using wristband PPG devices for HRV, and suggest chest- or earlobe-based ambulatory sensors and improved motion-correction algorithms as promising alternatives.
How to cite
APA
Ryan, W. S., Conigrave, J., Basarkod, G., Ciarrochi, J., & Sahdra, B. K. (2019). When is it good to use wristband devices to measure HRV? Introducing a new method for evaluating the quality of data from photoplethysmography-based HRV devices [Manuscript]. PsyArXiv.
BibTeX
@article{ryan2019when,
author = {Ryan, William S. and Conigrave, James and Basarkod, Geetanjali and Ciarrochi, Joseph and Sahdra, Baljinder K.},
title = {When is it good to use wristband devices to measure HRV? Introducing a new method for evaluating the quality of data from photoplethysmography-based HRV devices},
journal = {PsyArXiv (preprint)},
year = {2019}
}
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Author: Joseph Ciarrochi (ORCID 0000-0003-0471-8100). Free copy hosted with permission for scholarly use. Please cite the published version.