Comparing Heart Rate Variability with Polar H10 Sensor and Pulse Rate Variability with LYFAS: A Novel Study

Subhagata Chattopadhyay^1, and Rupam Das¹

¹Department of Research and Development (Digital Health), Acculi Labs Pvt. Ltd. Bangalore 560098, Karnataka India

Cite this paper:
Subhagata Chattopadhyay and Rupam Das. Comparing Heart Rate Variability with Polar H10 Sensor and Pulse Rate Variability with LYFAS: A Novel Study. Journal of Biomedical Engineering and Technology. 2021; 9(1):1-9. doi: 10.12691/jbet-9-1-1

Abstract

Background: Heart Rate Variability (HRV) surrogates for Cardiac Autonomic Modulation (CAM), while Pulse Rate variability (PRV) reflects Cardiovascular Autonomic Modulation (CvAM). HRV and PRV therefore, are not exactly interchangeable terms. However, the paper proposes that PRV and HRV can be correlated. Aim: To compare the correlation between two different instruments – (I) gold-standard Polar H10 HRV sensor that works on the principle of CAM and Kubios software for HRV estimation, together called ‘PK’ and (II) Lyfas smartphone application called ‘L’, which estimates PRV that reflects the state of CvAM. Methods: Parameters, such as (i) HR, (ii) RMSSD, (iii) pNN50, (iv) SDNN, and (v) LF/HF are captured from a total of 567 healthy Indian adults (312 males and 255 females) using PK and L simultaneously. End HR data (120 sec) are then compared instrument and gender-wise statistically by computing the i) RMSE, ii) Regressions (L on PK), iii) a Two-sample t-test, and (iv) classification accuracy of L when compared to PK. Finally, the Sensitivity/recall (R), Specificity (S), Precision (P), Accuracy (A), F score (F), and Youden’s index (Y) are computed for L. Results: L shows encouraging averages for males and females respectively ‘R’ (84%, 70%), ‘S’ (95%, 87%), ‘A’ (82%, 79%), ‘P’ (87%, 69%),’F’ (1.4836, 1.3706) and ‘Y’ (79%, 81%) for HR, SDNN, RMSSD, and pNN50 respectively. Conclusions: Although ‘L’ has 1/33th times less resolution compared to PK, its technical efficacy, speed, user-friendliness, low-cost-benefit, high ‘Y’ values, and ubiquitousness pose a great advantage in its deployment in the clinical setup as a biomarker tool over PK.

Keywords:
Heart Rate Variability Pulse Rate variability Polar H10 HRV sensor Kubios software Lyfas Youden’s index Biomarker Biofeedback

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References:

[1]	F. Shaffer, R. McCraty and C. L. Zerr, “A healthy heart is not a metronome: an integrative review of the heart's anatomy and heart rate variability,” Frontiers in Psychology, vol. 5, p. 1040, 2014.
[2]	“Pulse & Heart Rate,” [Online]. Available: https://my.clevelandclinic.org/health/diagnostics/17402-pulse--heart-rate.
[3]	R. McCraty and F. Shaffer, “Heart rate variability: new perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk,” Glob Adv Health Med , vol. 4, no. 1, pp. 46-61, 2015.
[4]	E. Morgan, “All About HRV Part 2: Interbeat Intervals and Time Domain Stats,” 24 September 2017. [Online]. Available: https://support.mindwaretech.com/2017/09/all-about-hrv-part-2-interbeat-intervals-and-time-domain-stats/. [Accessed 17 October 2021].
[5]	J. A. Waxenbaum, V. Reddy and M. Varacallo, Anatomy, Autonomic Nervous System., vol. 2, StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; , 2021.
[6]	R. N. Gevirtz, P. M. Lehrer and M. S. Schwartz, Biofeedback: A Practitioner’s Guide, 4th ed ed., A. F. Schwartz MS, Ed., New York: The Guilford Press, 2016, p. 196-213.
[7]	R. W. Levenson, “The Autonomic Nervous System and Emotion,” Sage Journals, 2014.
[8]	F. Beckers, B. Verheyden and A. E. Auburt, “Aging and nonlinear heart rate control in a healthy population,” Am J Physiol Heart Circ Physiol, vol. 290, no. 6, pp. H2560-H2570, 2006.
[9]	S. W. Weinschenk, R. D. Beise and J. Lorenz, “Heart rate variability (HRV) in deep breathing tests and 5-min short-term recordings: agreement of ear photoplethysmography with ECG measurements, in 343 subjects,” European Jpurnal of Applied Physiology, vol. 116, no. 8, p. 1527-35, 2016.
[10]	E. Yuda, M. Shibata, Y. Ogata, N. Ueda, T. Yambe, M. Yoshizawa and J. Hayano, “Pulse rate variability: a new biomarker, not a surrogate for heart rate variability,” Journal of Physiological Anthropology, vol. 39, no. 21, 2020.
[11]	M. Nardone, J. S. Floras and P. J. Millar, “Sympathetic neural modulation of arterial stiffness in humans,” American Journal of Physiology, 2020.
[12]	I. Antekmi, S. d. P. Rogerio, A. R. Shinzato, C. A. Peres, A. J. Mansur and e. al, “Influence of age, gender, body mass index, and functional capacity on heart rate variability in a cohort of subjects without heart disease,” The American Journal of Cardiology, vol. 93, no. 3, pp. 381-5, 2004.
[13]	N. K. Vaillancourt DE, “Changing complexity in human behavior and physiology through aging and disease.,” Neurobiology of Aging, vol. 23, no. 1, pp. 1-11, 2002.
[14]	D. Lucini, G. Norbiato, M. Clerici and M. Pagani, “Hemodynamic and Autonomic Adjustments to Real Life Stress Conditions in Humans,” Journal of the American Heart Association, vol. 39, no. 1, pp. 184-188, 2002.
[15]	H. G. N. Assoumou, V. Pichot, V. Dauphinot, S. Celle, P. Gosse, M. Kossovsky and e. al, “Metabolic Syndrome and Short-Term and Long-Term Heart Rate Variability in Elderly Free of Clinical Cardiovascular Disease: The PROOF Study,” Rejuvenation research, vol. 13, no. 6, pp. 653-63, 2010.
[16]	A. Sajadieh, O. W. Nielsen, V. Rasmussen and e. al, “Increased heart rate and reduced heart-rate variability are associated with subclinical inflammation in middle-aged and elderly subjects with no apparent heart disease,” European Heart Journal, vol. 25, no. 5, pp. 363-370, 2004.
[17]	E. Gellhorn, Autonomic Imbalance and the Hypthalamus: Implications for Physiology, Medicine, Psychology, and Neuropsychiatry, NED ed., University of Minnesota Press, 1957.
[18]	T. Nada, M. Nomura, A. Iga, R. Kawaguchi, Y. Ochi and K. Saito, “Autonomic nervous function in patients with peptic ulcer studied by spectral analysis of heart rate variability,” J Med, vol. 32, pp. 333-47, 2001.
[19]	R. D. Ballard, “Sleep, Respiratory Physiology, and Nocturnal asthma,” Chronobiology International, vol. 16, no. 5, pp. 565-580, 2009.
[20]	A. H. Zohar, C. R. Cloninger and R. McCraty, “Personality and Heart Rate Variability: Exploring Pathways from Personality to Cardiac Coherence and Health,” Open Journal of Social Sciences, vol. 1, no. 6, pp. 32-39, 2013.
[21]	C. L. Schaich, D. Malaver, H. Chen, H. A. Shaltout, A. Z. A. Hazzouri, D. M. Herrington and T. M. Hughes, “Association of Heart Rate Variability With Cognitive Performance: The Multi-Ethnic Study of Atherosclerosis,” Journal of the American Heart Association, vol. 9, no. 7, p. e013827, 2020.
[22]	C. M. Tyng, H. U. Amin, M. N. M. Saad and A. S. Malik, “The Influences of Emotion on Learning and Memory,” Front. Psychol., vol. 8, no. 1454, 2017.
[23]	E. Vanderveren, P. Bijttebier and D. Hermans, “The Importance of Memory Specificity and Memory Coherence for the Self: Linking Two Characteristics of Autobiographical Memory,” Front. Psychol., vol. 8, no. 2250, 2017.
[24]	H. S. Deepa and R. Das, “EVALUATION OF NON-INVASIVE SMARTPHONE BASED DIGITAL BIOMARKER TOOL LYFAS IN DETECTING SLEEP DEFICIENCY AND ITS EFFECTS: A RETROSPECTIVE OBSERVATIONAL STUDY,” Indian Journal of Applied Research, vol. 11, no. 1, pp. 46-47, 2021.
[25]	[Online]. Available: https://www.polar.com/blog/heart-rate-variability-and-orthostatic-test-lets-talk-polar/. [Accessed 09 October 2021].
[26]	[Online]. Available: https://www.kubios.com/scientific-research/. [Accessed 09 October 2021].
[27]	[Online]. Available: https://in.linkedin.com/company/acculi-labs. [Accessed 09 October 2021].
[28]	S. Cheriyedath, “Photoplethysmography (PPG),” 27 Feb 2019. [Online]. Available: https://www.news-medical.net/health/Photoplethysmography-(PPG).aspx. [Accessed 29 Sept 2021].
[29]	[Online]. Available: https://www.polar.com/en/products/accessories/H10_heart_rate_sensor. [Accessed 9 October 2021].
[30]	J. A. Lipponen and M. P. Tarvainen, “A robust algorithm for HRV time series artefact correction using novel beat classification.,” Journal of Medical Engineering & Technology, vol. 43, no. 3, pp. 173-181, 2019.
[31]	[Online]. Available: https://www.kubios.com/scientific-research/. [Accessed 09 October 2021].
[32]	M. Altini, “https://medium.com/,” 7 February 2020. [Online]. Available: https://medium.com/@altini_marco/the-ultimate-guide-to-heart-rate-variability-hrv-part-1-70a0a392fff4. [Accessed 15 October 2021].
[33]	K. Umetani, D. H. Singer, R. McCraty and M. Atkinson, “Twenty-Four Hour Time Domain Heart Rate Variability and Heart Rate: Relations to Age and Gender Over Nine Decades,” Journal of the American College of Cardiology, vol. 31, no. 3, pp. 593-601, 1998.
[34]	F. Shaffer and J. P. Ginsberg, “An Overview of Heart Rate Variability Metrics and Norms,” Frontiers in Public Health, vol. 28, no. 5, p. 258, 2017.
[35]	J. L. Francis, A. A. Weinstein, D. S. Krantz, M. C. Haigney, P. K. Stein, P. H. Stone, J. S. Gottdiener and W. J. Kop, “Association between Symptoms of Depression and Anxiety with Heart Rate Variability in Patients with Implantable Cardioverter Defibrillators,” Psychosomatic Medicine, vol. 71, no. 8, p. 821-827., 2009.
[36]	M. Yılmaz, H. Kayançiçek and Y. Çekici, “Heart rate variability: Highlights from hidden signals,” Journal of Integrative Cardiology, vol. 4, no. 5, pp. 1-8, 2018.
[37]	A. Ritter and R. Muñoz-Carpena, “Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments,” Journal of Hydrology, vol. 480, p. 33-45, 2013.
[38]	A. Ross and V. L. Willson, “Paired Samples T-Test.,” in Basic and Advanced Statistical Tests, Rotterdam, SensePublishers, 2017.
[39]	B. Griffiths, 8 October 2020. [Online]. Available: https://www.polar.com/blog/heart-rate-101/#:~:text=The%20average%20healthy%20adult%20will,RHR%20of%20around%2040%20BPM.. [Accessed 15 October 2021].
[40]	M. M. Corrales, B. d. l. C. Torres, A. G. Esquivel, M. A. G. Salazar and J. N. Orellana, “Normal values of heart rate variability at rest in a young, healthy and active Mexican population,” Scientific Research, vol. 4, no. 7, pp. 1-9, 2012.
[41]	E. Heidel, “Diagnosis,” scalesstatistics.com, 2021. [Online]. Available: https://www.scalestatistics.com/youden-index.html. [Accessed 02 Oct 2021].
[42]	D. G. Altman and J. M. Bland, “Measurement in medicine: the analysis of method comparison studies,” Statistician, vol. 32, p. 307-17, 1983.
[43]	D. Giavarina, “Understanding Bland Altman analysis,” Biochem Med (Zagreb), vol. 25, no. 2, p. 141-151., 2015.
[44]	G. J. Clement, “https://towardsdatascience.com/why-how-to-use-the-bland-altman-plot-for-a-b-testing-python-code-78712d28c362,” https://towardsdatascience.com, [Online]. Available: https://towardsdatascience.com/why-how-to-use-the-bland-altman-plot-for-a-b-testing-python-code-78712d28c362. [Accessed 14 October 2021].
[45]	Das, R.; Chatopadhyay S. “Towards Cardiac Risk Monitoring of Duchene Muscular Dystrophy using Lyfas”. Journal of Nanetechnology in Diagnosis and Treatment (2021), 7:25-32.