Abstract
The blood flow in human arterial system can be considered as a fluid dynamics problem. Simulation of blood flow will provide a better understanding of the physiology of human body. Simulation studies of blood flow in the diseased condition can help to diagnose the health problem easily and also have many applications in the areas such as surgical planning and design of medical devices. This paper presents a synthetic electrocardiogram (ECG), blood pressure signals (BP) and ballistocardiographic signal (BCG). Dynamical models of electrocardiogram and cardiovascular system are important in medicine because they can be used as approximation of the real patient. An example is the Windkessel model, which is often used for simulation. ECG, BP and BCG signals can be generated with different sampling frequencies, with different noise levels, with different shapes, filters etc. The paper is based on real data (Real data and identification methods can be used to create models), which are then used for models based on coupled oscillators. Models of the above-mentioned signals are generated by a microcontroller, which allows easy control and adjustment of the output signal and other experiments. The presented paper describes a device that was developed and used for educational purposes, especially for biomedical engineering.
Similar content being viewed by others
References
Formaggia, L., Quarteroni, A., & Veneziani, A. (2009). Cardiovascular mathematics - modeling and simulation of the circulatory system. . Springer.
Votta, E., Le, T. B., Stevanella, M., Fusinic, L., Caiani, E. G., Redaelli, A., & Sotiropoulos, F. (2013). Toward patient-specific simulations of cardiac valves: State-ofthe- art and future directions. Journal of Biomechanics, 46(2), 217–228.
Brunberg, A., Heinke, S., Spillner, J., Autschbach, R., Abel, D., & Leonhardt, S. (2009). Modeling and simulation of the cardiovascular system: A review of applications, methods, and potentials. Biomed Tech (Berl), 54, 233–244.
Korakianitis, T., & Shi, Y. (2006). A concentrated parameter model for the human cardiovascular system including heart valve dynamics and atrioventricular interaction. Medical Engineering & Physics, 28, 613–628.
Ferreira, A., Chen S., Galati, D., Simaan M. A., & J.F. Antaki, J. F., (2005). A dynamic state space representation and performance analysis of a feedback controlled rotary left ventricular assist device. In: Proceedings of the ASME 2005 - international mechanical engineering congress and exposition, Orlando, USA, November 5–11, 2005.
McSharry P. E., & Cifford G. D., (2004). Open-source software for generating electrocardiogram signals. arXiv:physics/0406017, Medical Physics.
Inan, O. T., Migeotte, P. F., Park, K. S., Tavakolian, M. E. K., Casanella, R., Zanetti, J., Tank, J., Funtova, I., Prisk, G. K., & Di Rienzo, M. (2015). Ballistocardiography and seismocardiography: A review of recent advances. IEEE Journal of Biomedical and Health Informatics, 19(4), 1414.
Stergiopulos, N., Westerhof, B. E., & Westerhof, N. (1999). Total arterial inertance as the fourth element of the windkessel model. American Journal of Physiology. Heart and Circulatory Physiology, 276, H81–H88.
J. Alastruey, J., Parker, K. H., & Sherwin S.J., (2012). Arterial pulse wave haemodynamics. In Anderson (Ed.) 11th international conference on pressure surges, chapter 7, pages 401–442. Virtual PiE Led t/a BHR Group (ISBN: 978 1 85598 133 1).
Peňáz, J. (1973). Photoelectric measurement of blood pressure, volume and flow in the finger. In: Albert R, Vogt WS, Helberg W, (Eds). Digest of the international conference on medicine and biological engineering. Dresden: conference committee of the X-th international conference on medicine and biological engineering
Wesseling, K. H., De Wit, B., Hoeven, V., et al. (1995). Physiocal, calibrating finger vascular physiology for Finapres. Homeostasis, 36, 67–82.
Salerno, D. M., & Zanetti, J. (1990). Seismocardiography: A new technique for recording cardiac vibrations. Concept, method, and initial observations. Journal of Cardiovascular Technology 9(2), 111–118.
Salerno, D. M., & Zanetti, J. (1991). Seismocardiography for monitoring left ventricular function during ischemia. Chest, 100(4), 991–993.
Dinh, A., (2011). Design of a seismocardiography using tri-axial accelerometer embedded with electrocardiogram. In: Proceedings of the world congress on engineering and computer science 2011 Vol II WCECS, San Francisco, USA. pp 782–785
Zanetti, J. M., & Tavakolian, K., (2013). Seismocardiography: Past, present and future. Paper presented at 35th annual international conference of the IEEE EMBS, Osaka, Japan, 3–7 July 2013.
Akhbardeh, A., Junnila, S., Koivistoinen, T., & Värri, A. (2007). An intelligent ballistocardiographic chair using a Novel SFART neural network and biorthogonal wavelets. Journal of Medical Systems, 31(1), 69–77.
PS410 - Patient Simulator. Retrieved from https://www.flukebiomedical.com/sites/default/ files/ resources/ps410_ENG_B_W.PDF
Phantom 320 ECG Simulator. Retrieved from https://www.ms-gmbh.de/en/produkt/phantom-320-ecg-simulator-english-variant.
CardioSim VII. Retrieved from http://www.survivaltechnology.com/pebble.asp?relid=36344.
Burattini, R., & Di Salvia, P. O. (2007). Development of systemic arterial mechanical properties from infancy to adulthood interpreted by four-element windkessel models. Journal of Applied Physiology, 103, 66–79.
NIBP-1020 Simulator. Retrieved from http://www.bcgroupstore.com/Biomedical-BC_Biomedical_NIBP-1020.aspx.
NIBP10_00 Simulator. Retrieved from http://bcgroupintl.com/BC_Biomedical_Manuals/pdf/BCBiomedicalNIBP1000_UM_Rev06.pdf.
MicroSim COS Cardiac output simulator. Retrieved from http://www.bionetics.ca/BNmicrosim_coscardiac_output_simu.htm.
MicroSim prosim8. Retrieved from https://www.metlog-biomed.eu/cms/upload/datenblaetter/prosim8_man_engl.pdf.
Ngai, B., Tavakolia K., Akhbardeh, A., Blaber A., & Kaminska B., (2009). Comparative analysis of seismocardiogram waves with the ultra-low frequency ballistocardiogram. Paper presented at 31st IEEE Engineering in Medicine and Biological Conference, pp 2851–2854.
Trefny Z., & Stork M., (2005) A system for noninvasive portable quantitative seismocardiographic signal evaluation. In: Proceedings of the IFMBE 3rd European Medical and Biological Engineering Conference. EMBEC 05, Prague, Czech Republic, 2005, vol. 11(1) pp 732–735.
Trefny, Z., Stork, M., & Trefny, M (2009). Electronic device for seismocardiography - noninvasive examination and signal evaluation. In: Proceedings of the International Conference on Biomedical Electronics and Devices - Volume 1: BIODEVICES, Porto, Portugal, pp. 204–208.
Stork, M., (2017). Simulation of ECG and cardiovascular system. Paper presented at 6th Mediterranean Conference on Embedded Computing (MECO), Bar, Montenegro.
AT91SAM - ARM-based Flash MCU. Retrieved from http://image.dfrobot.com/image/data/DFR0220/AT91SAM%20full%20datasheet.pdf.
MAX536/MAX537 - Calibrated, Quad, 12-bit voltage-output DACS with serial interface. Retrieved from https://datasheets.maximintegrated.com/en/ds/MAX536-MAX537.pdf.
Acknowledgements
This work was supported by Department of Electronics and Information Technology, University of West Bohemia, Plzen, Czech Republic and by the Ministry of Education, Youth and Sports of the Czech Republic under the project OP VVV Electrical Engineering Technologies with High-Level of Embedded Intelligence, CZ.02.1.01/0.0/0.0/18_069/ 0009855 and by the Internal Grant Agency of University of West Bohemia in Plzen, the project SGS-2018-001.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Stork, M. Simulation of ECG, blood pressure and ballistocardiographic signals. Analog Integr Circ Sig Process 108, 111–117 (2021). https://doi.org/10.1007/s10470-021-01830-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10470-021-01830-1