A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability

PLOS ONE RESEARCH ARTICLE A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability Fatemeh Sarhaddi ID1☯*, Kianoosh Kazemi1☯, Iman Azimi1,2, Rui Cao3, Hannakaisa NielaVilén4, Anna Axelin4,5, Pasi Liljeberg1, Amir M. Rahmani2,3,6 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Sarhaddi F, Kazemi K, Azimi I, Cao R, Niela-Vilén H, Axelin A, et al. (2022) A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability. PLoS ONE 17(12): e0268361. https://doi.org/ 10.1371/journal.pone.0268361 Editor: Saeed Mian Qaisar, Effat University, SAUDI ARABIA Received: April 26, 2022 Accepted: November 19, 2022 Published: December 8, 2022 Copyright: © 2022 Sarhaddi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The data used in this study include sensitive health information, and the informed consent signed by the participants does not allow the data to be made publicly available due to ethical restriction. According to the current approval by the Ethics Committee of University of Turku, the participants gave permission to use the collected data only for the purpose described in the consent. Data requests may be subject to individual consent and/or ethics committee approval. Researchers wishing to use the data should contact the Ethics Committee of University of 1 Department of Computing, University of Turku, Turku, Finland, 2 Institute for Future Health (IFH), University of California, Irvine, California, United States of America, 3 Department of Electrical Engineering and Computer Science, University of California, Irvine, California, United States of America, 4 Department of Nursing Science, University of Turku, Turku, Finland, 5 Department of Obstetrics and Gynaecology, Turku University Hospital and Faculty of Medicine, University of Turku, Turku, Finland, 6 School of Nursing, University of California, Irvine, California, United States of America ☯ These authors contributed equally to this work. * Abstract Background Photoplethysmography (PPG) is a low-cost and easy-to-implement method to measure vital signs, including heart rate (HR) and pulse rate variability (PRV) which widely used as a substitute of heart rate variability (HRV). The method is used in various wearable devices. For example, Samsung smartwatches are PPG-based open-source wristbands used in remote well-being monitoring and fitness applications. However, PPG is highly susceptible to motion artifacts and environmental noise. A validation study is required to investigate the accuracy of PPG-based wearable devices in free-living conditions. Objective We evaluate the accuracy of PPG signals—collected by the Samsung Gear Sport smartwatch in free-living conditions—in terms of HR and time-domain and frequency-domain HRV parameters against a medical-grade chest electrocardiogram (ECG) monitor. Methods We conducted 24-hours monitoring using a Samsung Gear Sport smartwatch and a Shimmer3 ECG device. The monitoring included 28 participants (14 male and 14 female), where they engaged in their daily routines. We evaluated HR and HRV parameters during the sleep and awake time. The parameters extracted from the smartwatch were compared against the ECG reference. For the comparison, we employed the Pearson correlation coefficient, Bland-Altman plot, and linear regression methods. PLOS ONE | https://doi.org/10.1371/journal.pone.0268361 December 8, 2022 1 / 19 PLOS ONE Turku, contact details: FI-20014 Turun yliopisto, Finland, e-mail: . We recommend first to contact the PI of the research project, associate professor Anna Axelin, contact details: University of Turku, Department of Nursing Science, 20014 University of Turku, Finland, e-mail: . Accuracy assessment of Samsung smartwatch HR and HRV Results Funding: This research was supported by the Academy of Finland https://www.aka.fi/en/ (Awards 316810 (AMR), and 316811 (AA)) and U.S. National Science Foundation https://www.nsf.gov/ (Awards CNS-1831918 and FW-HTF CNS2026614) (AMR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We found a significantly high positive correlation between the smartwatch’s and Shimmer ECG’s HR, time-domain HRV, LF, and HF and a significant moderate positive correlation between the smartwatch’s and shimmer ECG’s LF/HF during sleep time. The mean biases of HR, time-domain HRV, and LF/HF were low, while the biases of LF and HF were moderate during sleep. The regression analysis showed low error variances of HR, AVNN, and pNN50, moderate error variances of SDNN, RMSSD, LF, and HF, and high error variances of LF/HF during sleep. During the awake time, there was a significantly high positive correlation of AVNN and a moderate positive correlation of HR, while the other parameters indicated significantly low positive correlations. RMSSD and SDNN showed low mean biases, and the other parameters had moderate mean biases. In addition, AVNN had moderate error variance while the other parameters indicated high error variances. Competing interests: The authors have declared that no competing interests exist. Conclusion The Samsung smartwatch provides acceptable HR, time-domain HRV, LF, and HF parameters during sleep time. In contrast, during the awake time, AVNN and HR show satisfactory accuracy, and the other HRV parameters have high errors. Introduction Heart rate (HR) and heart rate variability (HRV) are physiological parameters reflecting autonomous nervous system regulations and general well-being. HR shows the number of heartbeats per minute, and HRV indicates the variation of time between two consecutive heartbeats or interbeat intervals (IBIs) [1]. Various HRV parameters can be extracted from IBIs, such as average normal IBIs (AVNN), standard deviation of normal IBIs (SDNN), and root mean square of the successive difference (RMSSD). HR and HRV parameters can provide insight into cardiovascular and autonomic nerve dysfunction [2]. Studies in the literature show the relationship between HRV parameters and different health issues such as diabetes [3], hypertension [4], depression [5], and autonomic imbalance [6]. Moreover, HRV parameters are associated with mental and physiological stress [7, 8], and sleep quality [9]. HR and HRV can be monitored using noninvasive methods such as Electrocardiography (ECG) and Photoplethysmography (PPG). ECG is the golden standard for HR and HRV parameters monitoring used in clinical trials. The method measures the electrical activity of the cardiovascular system using electrodes connected to the skins. However, it cannot be employed in home-based and/or long-term monitoring when people are engaged in dif (...truncated)