Healthy Young POLes – HYPOL database with synchronised beat-to-beat heart rate and blood pressure signals

HYPOL – Cardiovascular Time Series Database

Authors

DOI:

https://doi.org/10.20883/medical.e941

Keywords:

data sharing, cardiovascular time series, RR intervals, blood pressure, interbeat intervals, healthy young people

Abstract

Data sharing in medical research entails making research data available to other researchers for review, reuse, and collaboration. This paper seeks to describe the HYPOL (Healthy Young POLes) database, which has been prepared for sharing. This database houses the clinical characteristics and beat-to-beat cardiovascular time series of 278 individuals of Polish descent, all aged between 19 and 30 years. The data were collected from healthy volunteers who participated in multiple projects at the Department of Cardiology-Intensive Therapy research laboratory, Poznan University of Medical Sciences, Poznan, Poland. The cardiovascular time series data was obtained from non-invasive continuous finger blood pressure and ECG recordings, with sessions lasting up to 45 minutes. The HYPOL database includes an xls file detailing the main clinical characteristics and text files that capture ECG-derived RR intervals, finger systolic, diastolic, and mean blood pressure values, as well as the duration of interbeat intervals.
The data is from 149 women (53.6% of the total) and 129 men. The median age of all participants studied was 24 years, their BMI was <24 kg/m2, pulse rate and blood pressure were average. The median duration of the recordings was almost 30 minutes. In addition, we summarise selected parameters of heart rate variability (HRV) and heart rate asymmetry (HRA).
The HYPOL database is available at hypol.ump.edu.pl. The download of data is free after simple registration. Researchers and engineers can use the database to test various mathematical algorithms for HRV, HRA, blood pressure variability and asymmetry, and baroreflex function, except for selling it.

Downloads

Download data is not yet available.

Author Biography

  • Przemysław Guzik, Department of Cardiology-Intensive Therapy and Internal Medicine, Poznan University of Medical Sciences, Poland

    Przemyslaw Guzik, MD, PhD
    Department of Cardiology – Intensive Therapy
    Poznan University of Medical Sciences
    Przybyszewskiego 49
    60-355 Poznan, Poland
    pguzik@ptkardio.pl

References

Ohmann C, Banzi R, Canham S, Battaglia S, Matei M, Ariyo C, Becnel L, Bierer B, Bowers S, Clivio L, Dias M, Druml C, Faure H, Fenner M, Galvez J, Ghersi D, Gluud C, Groves T, Houston P, Karam G, Kalra D, Knowles RL, Krleža-Jerić K, Kubiak C, Kuchinke W, Kush R, Lukkarinen A, Marques PS, Newbigging A, O'Callaghan J, Ravaud P, Schlünder I, Shanahan D, Sitter H, Spalding D, Tudur-Smith C, van Reusel P, van Veen EB, Visser GR, Wilson J, Demotes-Mainard J. Sharing and reuse of individual participant data from clinical trials: principles and recommendations. BMJ Open. 2017;7:e018647. doi: 10.1136/bmjopen-2017-018647

Tenopir C, Allard S, Douglass K, Aydinoglu AU, Wu L, Read E, Manoff M, Frame M. Data sharing by scientists: practices and perceptions. PLoS One. 2011;6:e21101. doi: 10.1371/journal.pone.0021101

Popkin G. Data sharing and how it can benefit your scientific career. Nature. 2019;569:445-447. doi: 10.1038/d41586-019-01506-x

Tenopir C, Rice NM, Allard S, Baird L, Borycz J, Christian L, Grant B, Olendorf R, Sandusky RJ. Data sharing, management, use, and reuse: Practices and perceptions of scientists worldwide. PLoS One. 2020;15:e0229003. doi: 10.1371/journal.pone.0229003

Johnson AE, Pollard TJ, Shen L, Lehman LW, Feng M, Ghassemi M, Moody B, Szolovits P, Celi LA, Mark RG. MIMIC-III, a freely accessible critical care database. Sci Data. 2016;3:160035. doi: 10.1038/sdata.2016.35

Pollard TJ, Johnson AEW, Raffa JD, Celi LA, Mark RG, Badawi O. The eICU Collaborative Research Database, a freely available multi-center database for critical care research. Sci Data. 2018;5:180178. doi: 10.1038/sdata.2018.178

Young T, Shahar E, Nieto FJ, Redline S, Newman AB, Gottlieb DJ, Walsleben JA, Finn L, Enright P, Samet JM; Sleep Heart Health Study Research Group. Predictors of sleep-disordered breathing in community-dwelling adults: the Sleep Heart Health Study. Arch Intern Med. 2002;162:893-900. doi: 10.1001/archinte.162.8.893

Wang L, Zhou X. Detection of Congestive Heart Failure Based on LSTM-Based Deep Network via Short-Term RR Intervals. Sensors (Basel). 2019;19:1502. doi: 10.3390/s19071502

Papini GB, Fonseca P, Margarito J, van Gilst MM, Overeem S, Bergmans JWM, Vullings R. On the generalizability of ECG-based obstructive sleep apnea monitoring: merits and limitations of the Apnea-ECG database. Annu Int Conf IEEE Eng Med Biol Soc. 2018;2018:6022-6025. doi: 10.1109/EMBC.2018.8513660

Costa M, Moody GB, Henry I, Goldberger AL. PhysioNet: an NIH research resource for complex signals. J Electrocardiol. 2003;36 Suppl:139-44. doi: 10.1016/j.jelectrocard.2003.09.038

Moody GB, Mark RG, Goldberger AL. PhysioNet: physiologic signals, time series and related open source software for basic, clinical, and applied research. Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:8327-30. doi: 10.1109/IEMBS.2011.6092053

Ghassemi MM, Moody BE, Lehman LH, Song C, Li Q, Sun H, Mark RG, Westover MB, Clifford GD. You Snooze, You Win: the PhysioNet/Computing in Cardiology Challenge 2018;45:10.22489/cinc.2018.049. doi: 10.22489/cinc.2018.049

Hong S, Zhang W, Sun C, Zhou Y, Li H. Practical Lessons on 12-Lead ECG Classification: Meta-Analysis of Methods From PhysioNet/Computing in Cardiology Challenge 2020. Front Physiol. 2022;12:811661. doi: 10.3389/fphys.2021.811661

Buś S, Jędrzejewski K, Guzik P. A New Approach to Detecting Atrial Fibrillation Using Count Statistics of Relative Changes between Consecutive RR Intervals. J Clin Med. 2023;12:687. doi: 10.3390/jcm12020687

Buś S, Jędrzejewski K, Guzik P. Statistical and Diagnostic Properties of pRRx Parameters in Atrial Fibrillation Detection. J Clin Med. 2022;11:5702. doi: 10.3390/jcm11195702

Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Eur Heart J. 1996;17:354-81. PMID: 8737210.

Sassi R, Cerutti S, Lombardi F, Malik M, Huikuri HV, Peng CK, Schmidt G, Yamamoto Y. Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society. Europace. 2015;17:1341-53. doi: 10.1093/europace/euv015

Parati G, Bilo G, Kollias A, Pengo M, Ochoa JE, Castiglioni P, Stergiou GS, Mancia G, Asayama K, Asmar R, Avolio A, Caiani EG, De La Sierra A, Dolan E, Grillo A, Guzik P, Hoshide S, Head GA, Imai Y, Juhanoja E, Kahan T, Kario K, Kotsis V, Kreutz R, Kyriakoulis KG, Li Y, Manios E, Mihailidou AS, Modesti PA, Omboni S, Palatini P, Persu A, Protogerou AD, Saladini F, Salvi P, Sarafidis P, Torlasco C, Veglio F, Vlachopoulos C, Zhang Y. Blood pressure variability: methodological aspects, clinical relevance and practical indications for management - a European Society of Hypertension position paper. J Hypertens. 2023;41:527-544. doi: 10.1097/HJH.0000000000003363

Guzik P, Piskorski J. Asymmetric properties of heart rate microstructure. J. Med. Sci. 2020;89:e436. doi: 10.20883/medical.e436

Costa MD, Davis RB, Goldberger AL. Heart Rate Fragmentation: A New Approach to the Analysis of Cardiac Interbeat Interval Dynamics. Front Physiol. 2017;8:255. doi: 10.3389/fphys.2017.00255

Guzik P, Wykretowicz A, Wesseling IK, Wysocki H. Adrenal pheochromocytoma associated with dramatic cyclic hemodynamic fluctuations. Int J Cardiol. 2005;103:351-3. doi: 10.1016/j.ijcard.2004.08.071

Guzik P, Piskorski J, Ellert J, Krauze T. Asymmetry of haemodynamic variability in healthy people, 2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), Trento, Italy, 2014, pp. 129-130, doi: 10.1109/ESGCO.2014.6847553

Guzik P, Piskorski J, Krauze T, Schneider R, Wesseling KH, Wykretowicz A, Wysocki H. Correlations between the Poincaré plot and conventional heart rate variability parameters assessed during paced breathing. J Physiol Sci. 2007;57:63-71. doi: 10.2170/physiolsci.RP005506

Sesso HD, Stampfer MJ, Rosner B, Hennekens CH, Gaziano JM, Manson JE, Glynn RJ. Systolic and diastolic blood pressure, pulse pressure, and mean arterial pressure as predictors of cardiovascular disease risk in Men. Hypertension. 2000;36:801-7. doi: 10.1161/01.hyp.36.5.801

Kim DH, Shin S, Kim JY, Kim SH, Jo M, Choi YS. Pulse pressure variation and pleth variability index as predictors of fluid responsiveness in patients undergoing spinal surgery in the prone position. Ther Clin Risk Manag. 2018;14:1175-1183. doi: 10.2147/TCRM.S170395

Geeganage C, Tracy M, England T, Sare G, Moulin T, Woimant F, Christensen H, De Deyn PP, Leys D, O'Neill D, Ringelstein EB, Bath PM; for TAIST Investigators. Relationship between baseline blood pressure parameters (including mean pressure, pulse pressure, and variability) and early outcome after stroke: data from the Tinzaparin in Acute Ischaemic Stroke Trial (TAIST). Stroke. 2011;42:491-3. doi: 10.1161/STROKEAHA.110.596163

Maïer B, Turc G, Taylor G, Blanc R, Obadia M, Smajda S, Desilles JP, Redjem H, Ciccio G, Boisseau W, Sabben C, Ben Machaa M, Hamdani M, Leguen M, Gayat E, Blacher J, Lapergue B, Piotin M, Mazighi M; Endovascular Treatment in Ischemic Stroke (ETIS) Investigators. Prognostic Significance of Pulse Pressure Variability During Mechanical Thrombectomy in Acute Ischemic Stroke Patients. J Am Heart Assoc. 2018;7:e009378. doi: 10.1161/JAHA.118.009378

Krauze T, Liberkowska M, Adamska K, Turska E, Wykrętowicz A, Guzik P. Acute hemodynamic effects of salted potato chips in healthy people. Pol Arch Intern Med. 2019;129:721-724. doi: 10.20452/pamw.14935

Obeid H, Tairi A, Fortier C, Giudici A, Spronck B, Agharazii M. Carotid-femoral pulse wave velocity variability: beat-to-beat assessment. J Hypertens. 2023;41(Suppl 3):e268. doi: 10.1097/01.hjh.0000941768.60309.c1

Svačinová J, Hrušková J, Jakubík J, Budinskaya K, Hidegová S, Fabšík M, Sieglová H, Kaščáková Z, Novák J, Nováková Z. Variability of peripheral pulse wave velocity in patients with diabetes mellitus type 2 during orthostatic challenge. Physiol Res. 2020;69(Suppl 3):S433-S441. doi: 10.33549/physiolres.934594

Triedman JK, Saul JP. Blood pressure modulation by central venous pressure and respiration. Buffering effects of the heart rate reflexes. Circulation. 1994;89:169-79. doi: 10.1161/01.cir.89.1.169

Zareba W, Bayes de Luna A. QT dynamics and variability. Ann Noninvasive Electrocardiol. 2005;10:256-62. doi: 10.1111/j.1542-474X.2005.10205.x

Guzik P, Zuchowski B, Blaszyk K, Seniuk W, Wasniewski M, Gwizdala A, Wykretowicz A, Piskorski J. Asymmetry of the variability of heart rate and conduction time between atria and ventricles. Circ J. 2013;77:2904-11. doi: 10.1253/circj.cj-13-0461

Żuchowski B, Błaszyk K, Piskorski J, Wykrętowicz A, Guzik P. Dependence of the Atrioventricular Conduction Time on the Conduction through the Atrioventricular Node and His-Purkinje System. J Clin Med. 2023;12:1330. doi: 10.3390/jcm12041330

Guzik P, Piskorski J, Barthel P, Bauer A, Müller A, Junk N, Ulm K, Malik M, Schmidt G. Heart rate deceleration runs for postinfarction risk prediction. J Electrocardiol. 2012;45:70-6. doi: 10.1016/j.jelectrocard.2011.08.006

Bauer A, Guzik P, Barthel P, Schneider R, Ulm K, Watanabe MA, Schmidt G. Reduced prognostic power of ventricular late potentials in post-infarction patients of the reperfusion era. Eur Heart J. 2005;26:755-61. doi: 10.1093/eurheartj/ehi101

Bishop SA, Dech RT, Guzik P, Neary JP. Heart rate variability and implication for sport concussion. Clin Physiol Funct Imaging. 2018;38:733-742. doi: 10.1111/cpf.12487

Kaczmarek LD, Behnke M, Enko J, Kosakowski M, Hughes BM, Piskorski J, Guzik P. Effects of emotions on heart rate asymmetry. Psychophysiology. 2019;56:e13318. doi: 10.1111/psyp.13318

Kaczmarek LD, Behnke M, Kosakowski M, Enko J, Dziekan M, Piskorski J, Hughes BM, Guzik P. High-approach and low-approach positive affect influence physiological responses to threat and anger. Int J Psychophysiol. 2019 ;138:27-37. doi: 10.1016/j.ijpsycho.2019.01.008

Guzik P, Piekos C, Pierog O, Fenech N, Krauze T, Piskorski J, Wykretowicz A. Classic electrocardiogram-based and mobile technology derived approaches to heart rate variability are not equivalent. Int J Cardiol. 2018;258:154-156. doi: 10.1016/j.ijcard.2018.01.056

Guzik P, Piskorski J, Krauze T, Wykretowicz A, Wysocki H. Heart rate asymmetry by Poincaré plots of RR intervals. Biomed Tech (Berl). 2006;51:272-5. doi: 10.1515/BMT.2006.054

Piskorski J, Guzik P. Geometry of the Poincaré plot of RR intervals and its asymmetry in healthy adults. Physiol Meas. 2007;28:287-300. doi: 10.1088/0967-3334/28/3/005

Piskorski J, Guzik P. Asymmetric properties of long-term and total heart rate variability. Med Biol Eng Comput. 2011;49:1289-97. doi: 10.1007/s11517-011-0834-z

Piskorski J, Guzik P. The structure of heart rate asymmetry: deceleration and acceleration runs. Physiol Meas. 2011;32:1011-23. doi: 10.1088/0967-3334/32/8/002

Piskorski J, Kośmider M, Mieszkowski D, Żurek S, Biczuk B, Jurga S, Krauze T, Wykrętowicz A, Guzik P. Associations between heart rate asymmetry expression and asymmetric detrended fluctuation analysis results. Med Biol Eng Comput. 2022;60:2969-2979. doi: 10.1007/s11517-022-02645-6

Piskorski J, Ellert J, Krauze T, Grabowski W, Wykretowicz A, Guzik P. Testing heart rate asymmetry in long, nonstationary 24 hour RR-interval time series. Physiol Meas. 2019;40:105001. doi: 10.1088/1361-6579/ab42d5

Sibrecht G, Piskorski J, Krauze T, Guzik P. Heart Rate Asymmetry, Its Compensation, and Heart Rate Variability in Healthy Adults during 48-h Holter ECG Recordings. J Clin Med. 2023;12:1219. doi: 10.3390/jcm12031219

Zalas D, Bobkowski W, Piskorski J, Guzik P. Heart Rate Asymmetry in Healthy Children. J Clin Med. 2023;12:1194. doi: 10.3390/jcm12031194

Piskorski J, Guzik P. Compensatory properties of heart rate asymmetry. J Electrocardiol. 2012;45:220-4. doi: 10.1016/j.jelectrocard.2012.02.001

Guzik P, Piskorski J, Krauze T, Narkiewicz K, Wykretowicz A, Wysocki H. Asymmetric features of short-term blood pressure variability. Hypertens Res. 2010;33:1199-205. doi: 10.1038/hr.2010.138

Parati G, Di Rienzo M, Mancia G. How to measure baroreflex sensitivity: from the cardiovascular laboratory to daily life. J Hypertens. 2000;18:7-19. PMID: 10678538.

Westerhof BE, Gisolf J, Stok WJ, Wesseling KH, Karemaker JM. Time-domain cross-correlation baroreflex sensitivity: performance on the EUROBAVAR data set. J Hypertens. 2004;22:1371-80. doi: 10.1097/01.hjh.0000125439.28861.ed

deBoer RW, Karemaker JM, Strackee J. Hemodynamic fluctuations and baroreflex sensitivity in humans: a beat-to-beat model. Am J Physiol. 1987;253:H680-9. doi: 10.1152/ajpheart.1987.253.3.H680

Katarzynska-Szymanska A, Ochotny R, Oko-Sarnowska Z, Wachowiak-Baszynska H, Krauze T, Piskorski J, Gwizdala A, Mitkowski P, Guzik P. Shortening baroreflex delay in hypertrophic cardiomyopathy patients -- an unknown effect of β-blockers. Br J Clin Pharmacol. 2013;75:1516-24. doi: 10.1111/bcp.12027

Adamska K, Krauze T, Guzik P, Piskorski J, Klimas K, Wykrętowicz A. Acute cardiovascular responses elicited by consumption of beer in healthy people. Pol Arch Intern Med. 2018;128:400-402. doi: 10.20452/pamw.4266

Kubiak KB, Więckowska B, Krauze T, Piskorski J, Guzik P. Detection of the baroreflex function changes during the 30-minute supine rest by the Poincaré plot-based method, 2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), Vysoké Tatry, Štrbské Pleso, Slovakia, 2022, pp. 1-2, doi: 10.1109/ESGCO55423.2022.9931378.

Kubiak KB, Więckowska B, Krauze T, Piskorski J, Guzik P. Detection of the baroreflex function changes during the 30-minute supine rest by the Poincaré plot-based method, 2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), Vysoké Tatry, Štrbské Pleso, Slovakia, 2022, pp. 1-2, doi: 10.1109/ESGCO55423.2022.9931378.

Sawicka-Gutaj N, Gruszczyński D, Guzik P, Mostowska A, Walkowiak J. Publication ethics of human studies in the light of the Declaration of Helsinki—A mini-review. J. Med. Sci. 2022, 91, e700. doi: 0000-0001-9052-5027

Schneider R, Bauer A, Barthel P, Schmidt G. libRASCH: a programming framework for signal handling. Comput in Cardiol. 2004; Chicago, IL, USA, 2004, pp. 53-56, doi: 10.1109/CIC.2004.1442869

Wykretowicz A, Metzler L, Milewska A, Balinski M, Rutkowska A, Adamska K, Krauze T, Guzik P, Dziarmaga M, Wysocki H. Noninvasively assessed pulsatility of ascending aortic pressure waveform is associated with the presence of coronary artery narrowing. Heart Vessels. 2008;23:16-9. doi: 10.1007/s00380-007-1003-z

Guzik P, Piskorski J, Krauze T, Wykretowicz A, Wysocki H. Partitioning total heart rate variability. Int J Cardiol. 2010;144:138-9. doi: 10.1016/j.ijcard.2008.12.151

Lomb NR. Least-squares frequency analysis of unequally spaced data. Astrophys Space Sci. 1976;39:447–462. doi: 10.1007/BF00648343

Moody GB. Spectral analysis of heart rate without resampling. Proceedings of Computers in Cardiology Conference, London, UK, 1993, pp. 715-718, doi: 10.1109/CIC.1993.378302.

Laguna P, Moody GB, Mark RG. Power spectral density of unevenly sampled data by least-square analysis: performance and application to heart rate signals. IEEE. Trans. Biomed. Eng. 1998;45:698–715. doi: 10.1109/10.678605

Piskorski J, Guzik P, Krauze T, Zurek S. Cardiopulmonary resonance at 0.1 Hz demonstrated by averaged Lomb-Scargle periodogram. Cent. Eur. J. Physics 2010;8:386–392. doi: 10.2478/s11534-009-0101-1

Bobkowski W, Stefaniak ME, Krauze T, Gendera K, Wykretowicz A, Piskorski J, Guzik P. Measures of Heart Rate Variability in 24-h ECGs Depend on Age but Not Gender of Healthy Children. Front Physiol. 2017;8:311. doi: 10.3389/fphys.2017.00311

Porta A, Casali KR, Casali AG, Gnecchi-Ruscone T, Tobaldini E, Montano N, Lange S, Geue D, Cysarz D, Van Leeuwen P. Temporal asymmetries of short-term heart period variability are linked to autonomic regulation. Am J Physiol Regul Integr Comp Physiol. 2008;295:R550-7. doi: 10.1152/ajpregu.00129.2008

Guzik P, Więckowska B. Data distribution analysis—A preliminary approach to quantitative data in biomedical research. J. Med. Sci. 2023;92:e869. doi: 10.20883/medical.e869

Bus S, Jedrzejewski K, Krauze T, Guzik P. Experimental comparison of photoplethysmography-based atrial fibrillation detection using simple machine learning methods. Proceedings of SPIE - The International Society for Optical Engineering. 2020. DOI: 10.1117/12.2580594

Kotecha D, Chua WWL, Fabritz L, Hendriks J, Casadei B, Schotten U, Vardas P, Heidbuchel H, Dean V, Kirchhof P; European Society of Cardiology (ESC) Atrial Fibrillation Guidelines Taskforce, the CATCH ME consortium and the European Heart Rhythm Association (EHRA). European Society of Cardiology smartphone and tablet applications for patients with atrial fibrillation and their health care providers. Europace. 2018;20:225-233. doi: 10.1093/europace/eux299

Downloads

Published

2023-11-13

Issue

Section

Original Papers

How to Cite

1.
Guzik P, Krauze T, Wykrętowicz A, Piskorski J. Healthy Young POLes – HYPOL database with synchronised beat-to-beat heart rate and blood pressure signals: HYPOL – Cardiovascular Time Series Database. JMS [Internet]. 2023 Nov. 13 [cited 2024 Dec. 21];92(4):e941. Available from: https://jmsnew.ump.edu.pl/index.php/JMS/article/view/941