Smartwatch-derived heart rate variability: a head-to-head comparison with the gold standard in cardiovascular disease
Author: Fabian Theurl1, Michael Schreinlechner1, Nikolay Sappler1, Michael Toifl1, Theresa Dolejsi1, Florian Hofer1, Celine Massmann1, Christian Steinbring1, Silvia Komarek2,3, Kurt Mölgg2,3, Benjamin Dejakum2,3, Christian Böhme2, Rudolf Kirchmair1, Sebastian Reinstadler1, Axel Bauer1
Affiliation:
1 Department of Internal Medicine III-Cardiology and Angiology, Medical University of Innsbruck, Anichstr. 35, Innsbruck 6020, Austria.
2 Department of Neurology, Medical University of Innsbruck, Anichstr. 35, Innsbruck 6020, Austria.
3 Research Centre on Vascular Ageing and Stroke (VASCage), Anichstr. 5a, Innsbruck 6020, Austria.
Conference/Journal: Eur Heart J Digit Health
Date published: 2023 Mar 23
Other:
Volume ID: 4 , Issue ID: 3 , Pages: 155-164 , Special Notes: doi: 10.1093/ehjdh/ztad022. , Word Count: 244
Aims:
We aimed to investigate the concordance between heart rate variability (HRV) derived from the photoplethysmographic (PPG) signal of a commercially available smartwatch compared with the gold-standard high-resolution electrocardiogram (ECG)-derived HRV in patients with cardiovascular disease.
Methods and results:
We prospectively enrolled 104 survivors of acute ST-elevation myocardial infarction, 129 patients after an ischaemic stroke, and 30 controls. All subjects underwent simultaneous recording of a smartwatch (Garmin vivoactive 4; Garmin Ltd, Olathe, KS, USA)-derived PPG signal and a high-resolution (1000 Hz) ECG for 30 min under standardized conditions. HRV measures in time and frequency domain, non-linear measures, as well as deceleration capacity (DC) were calculated according to previously published technologies from both signals. Lin's concordance correlation coefficient (ρc) between smartwatch-derived and ECG-based HRV markers was used as a measure of diagnostic accuracy. A very high concordance within the whole study cohort was observed for the mean heart rate (ρc = 0.9998), standard deviation of the averages of normal-to-normal (NN) intervals in all 5min segments (SDANN; ρc = 0.9617), and very low frequency power (VLF power; ρc = 0.9613). In contrast, detrended fluctuation analysis (DF-α1; ρc = 0.5919) and the square mean root of the sum of squares of adjacent NN-interval differences (rMSSD; ρc = 0.6617) showed only moderate concordance.
Conclusion:
Smartwatch-derived HRV provides a practical alternative with excellent accuracy compared with ECG-based HRV for global markers and those characterizing lower frequency components. However, caution is warranted with HRV markers that predominantly assess short-term variability.
Keywords: Deceleration capacity; Heart rate variability; Smartwatch; Wearables.
PMID: 37265873 PMCID: PMC10232241 DOI: 10.1093/ehjdh/ztad022
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