Validation of Heart Rate Monitor Polar RS800 for Heart Rate Variability Analysis During Exercise

Abstract Hernando, D, Garatachea, N, Almeida, R, Casajús, JA, and Bailón, R. Validation of heart rate monitor Polar RS800 for heart rate variability analysis during exercise. J Strength Cond Res 32(3): 716–725, 2018—Heart rate variability (HRV) analysis during exercise is an interesting noninvasive tool to measure the cardiovascular response to the stress of exercise. Wearable heart rate monitors are a comfortable option to measure interbeat (RR) intervals while doing physical activities. It is necessary to evaluate the agreement between HRV parameters derived from the RR series recorded by wearable devices and those derived from an electrocardiogram (ECG) during dynamic exercise of low to high intensity. Twenty-three male volunteers performed an exercise stress test on a cycle ergometer. Subjects wore a Polar RS800 device, whereas ECG was also recorded simultaneously to extract the reference RR intervals. A time–frequency spectral analysis was performed to extract the instantaneous mean heart rate (HRM), and the power of low-frequency (PLF) and high-frequency (PHF) components, the latter centered on the respiratory frequency. Analysis was done in intervals of different exercise intensity based on oxygen consumption. Linear correlation, reliability, and agreement were computed in each interval. The agreement between the RR series obtained from the Polar device and from the ECG is high throughout the whole test although the shorter the RR is, the more differences there are. Both methods are interchangeable when analyzing HRV at rest. At high exercise intensity, HRM and PLF still presented a high correlation (&rgr; > 0.8) and excellent reliability and agreement indices (above 0.9). However, the PHF measurements from the Polar showed reliability and agreement coefficients around 0.5 or lower when the level of the exercise increases (for levels of O2 above 60%).

[1]  Mika P. Tarvainen,et al.  Effect of heart rate correction on pre- and post-exercise heart rate variability to predict risk of mortality—an experimental study on the FINCAVAS cohort , 2014, Front. Physiol..

[2]  Lloyd S. Nelson,et al.  Analysis of straight-line data , 1959 .

[3]  Patrick Flandrin,et al.  Wigner-Ville spectral analysis of nonstationary processes , 1985, IEEE Trans. Acoust. Speech Signal Process..

[4]  Matthias Weippert,et al.  Comparison of three mobile devices for measuring R–R intervals and heart rate variability: Polar S810i, Suunto t6 and an ambulatory ECG system , 2010, European Journal of Applied Physiology.

[5]  Olaf Hoos,et al.  [Heart rate variability and physical exercise. Current status]. , 2006, Herz.

[6]  Barbara Canlon,et al.  Possibilities and limitations of the polar RS800 in measuring heart rate variability at rest , 2011, European Journal of Applied Physiology.

[7]  Hein Heidbuchel,et al.  Normal electrocardiographic findings: recognising physiological adaptations in athletes , 2013, British Journal of Sports Medicine.

[8]  David R Hillman,et al.  Physiologic responses to incremental and self-paced exercise in COPD: a comparison of three tests. , 2004, Chest.

[9]  S. Bacon,et al.  Improvements in heart rate variability with exercise therapy. , 2010, The Canadian journal of cardiology.

[10]  Juan Pablo Martínez,et al.  QRS detectors performance comparison in public databases , 2014, Computing in Cardiology 2014.

[11]  J. Sacha Interaction between Heart Rate and Heart Rate Variability , 2014, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.

[12]  David Giles,et al.  Validity of the Polar V800 heart rate monitor to measure RR intervals at rest , 2015, European Journal of Applied Physiology.

[13]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[14]  Pablo Laguna,et al.  A wavelet-based ECG delineator: evaluation on standard databases , 2004, IEEE Transactions on Biomedical Engineering.

[15]  L. Lin,et al.  A concordance correlation coefficient to evaluate reproducibility. , 1989, Biometrics.

[16]  Jussi Mikkola,et al.  Effect of low-dose endurance training on heart rate variability at rest and during an incremental maximal exercise test , 2008, European Journal of Applied Physiology.

[17]  F. Gamelin,et al.  Validity of the Polar S810 to Measure R-R Intervals in Children , 2007, International journal of sports medicine.

[18]  Raquel Bailón,et al.  QRS detection optimization in stress test recordings using evolutionary algorithms , 2014, Computing in Cardiology 2014.

[19]  M. Kendall Statistical Methods for Research Workers , 1937, Nature.

[20]  A. Aubert,et al.  Heart Rate Variability in Athletes , 2003, Sports medicine.

[21]  C. M. Pastre,et al.  Comparison of Polar® RS800G3™ heart rate monitor with Polar® S810i™ and electrocardiogram to obtain the series of RR intervals and analysis of heart rate variability at rest , 2016, Clinical physiology and functional imaging.

[22]  E. Tolley,et al.  Qualitative Methods in Public Health: A Field Guide for Applied Research , 2004 .

[23]  David B. Kaber,et al.  Workload State Classification With Automation During Simulated Air Traffic Control , 2007 .

[24]  André Souto,et al.  Assessment of disagreement: a new information-based approach. , 2010, Annals of epidemiology.

[25]  M. Lambert,et al.  Autonomic Control of Heart Rate during and after Exercise , 2008, Sports medicine.

[26]  Matthias Weippert,et al.  Fuzzy Evaluation of Heart Rate Signals for Mental Stress Assessment , 2007, IEEE Transactions on Fuzzy Systems.

[27]  Pablo Laguna,et al.  Influence of time-varying mean heart rate in coronary artery disease diagnostic performance of heart rate variability indices from exercise stress testing. , 2011, Journal of electrocardiology.

[28]  R. D. Millsaps PRINCIPLES OF EXERCISE TESTING AND INTERPRETATION , 1987 .

[29]  G. RANGANATHAN,et al.  Evaluation of ECG Signals for Mental Stress Assessment using Fuzzy Technique , 2011 .

[30]  Pablo Laguna,et al.  Analysis of heart rate variability in the presence of ectopic beats using the heart timing signal , 2003, IEEE Transactions on Biomedical Engineering.

[31]  L. Sornmo,et al.  Analysis of Heart Rate Variability Using Time-Varying Frequency Bands Based on Respiratory Frequency , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[32]  Lino Nobili,et al.  Heart rate variability in normal and pathological sleep , 2013, Front. Physiol..

[33]  Luca T Mainardi,et al.  On the quantification of heart rate variability spectral parameters using time–frequency and time-varying methods , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[34]  Pablo Laguna,et al.  Influence of Running Stride Frequency in Heart Rate Variability Analysis During Treadmill Exercise Testing , 2013, IEEE Transactions on Biomedical Engineering.

[35]  Pablo Laguna,et al.  The Integral Pulse Frequency Modulation Model With Time-Varying Threshold: Application to Heart Rate Variability Analysis During Exercise Stress Testing , 2011, IEEE Transactions on Biomedical Engineering.

[36]  J. Sacha,et al.  Heart rate impact on the reproducibility of heart rate variability analysis. , 2013, International journal of cardiology.