Non-Invasive Blood Pressure Total Waveform Monitoring Using Information Extracted by an Extended Kalman Filter Algorithm from Pulsations in an Oscillatory Cuff
Main Article Content
Abstract
This paper describes a novel approach designed for non-invasive, routine screening of patients for cardiovascular disorders without the complexities of using an electrocardiogram or invasive probes. Specifically, an oscillographic-view of the brachial artery blood pressure waveform, including the dicrotic notch, is extracted from information in the pressure pulsations from an ordinary blood pressure cuff. The novelty of this approach is that the total continuous shape of the waveform, not just two numbers for pressures, is generated. A computer algorithm processes the cuff pressure pulsations and provides a near real-time visual estimate of the continuous shape of the blood pressure waveform to be viewed on oscilloscopes commonly used in hospitals and medical clinics. A model-based Extended Kalman Filter (EKF) algorithm is used to process the information and identify the coefficients of a Fourier transform model for the waveform and the coefficients for an empirical model for artery stiffness. By viewing the total waveform, variations or disorders in the waveform during a series of pulse cycles can be observed and easily recognized. Simulations of two-case studies demonstrate successful convergence of the algorithm for a variety of waveform disorders including arrhythmia, variations in the shape of the dicrotic notch, changing systolic and diastolic pressure levels, and stiff arteries. Experimental verification of this proposed procedure will require invasive pressure measurements while simultaneously processing the algorithm for non-invasive waveform comparisons. Once the algorithm is verified experimentally, the end goal is to use the procedure on patients with known cardiovascular diseases in order to easily create a database of waveform disorders correlated with disorders of specific cardiovascular diseases.
Article Details
How to Cite
HULLENDER, David A.; BROWN, Olen R.; SHROTRIYA, Atul.
Non-Invasive Blood Pressure Total Waveform Monitoring Using Information Extracted by an Extended Kalman Filter Algorithm from Pulsations in an Oscillatory Cuff.
Medical Research Archives, [S.l.], v. 11, n. 3, mar. 2023.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/3677>. Date accessed: 25 apr. 2024.
doi: https://doi.org/10.18103/mra.v11i3.3677.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
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26. Jain SK, Bhaumik B. An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone. IEEE Trans Biomed Circuits Syst. 2017;11(2). doi:10.1109/TBCAS.2016.2592382
27. Garcia D, Pibarot P, Kadem L, Durand LG. Respective impacts of aortic stenosis and systemic hypertension on left ventricular hypertrophy. J Biomech. 2007;40(5). doi:10.1016/j.jbiomech.2006.03.020
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32. Mills NL, Miller JJ, Anand A, et al. Increased arterial stiffness in patients with chronic obstructive pulmonary disease: a mechanism for increased cardiovascular risk. Published online 2007. doi:10.1136/thx.2007.083493
33. Sabbah HN, Stein PD. Valve origin of the aortic incisura. Am J Cardiol. 1978;41(1). doi:10.1016/0002-9149(78)90128-5
34. Mark JB. Atlas of Cardiovascular Monitoring. Churchill Livingstone Inc., New York, NY. 1998. ISBN:0-443-08891-8.
35. Judge TP, Kennedy JW. Estimation of aortic regurgitation by diastolic pulse wave analysis. Circulation. 1970;41(4). doi:10.1161/01.CIR.41.4.659
36. Shrotriya A. Analysis of Blood Pressure Waveform for Detection and Diagnosis of Cardiovascular Disorders. Dec. 12, 2021. Libraries Research Commons, University of Texas Arlington, dc.creator.orcid 0000-0002-5423-043X.
37. Jablonski I, Glomb G, Morello R. A Laboratory Set-up for Experimentation with the Cuffless Blood Pressure Measurement. In: IEEE Medical Measurements and Applications, MeMeA 2020 - Conference Proceedings. 2020. doi:10.1109/MeMeA49120.2020.913712
38. Sánchez R, Pessana F, Lev G, et al. Central Blood Pressure Waves Assessment: A Validation Study of Non-invasive Aortic Pressure Measurement in Human Beings. High Blood Pressure and Cardiovascular Prevention. 2020;27(2). doi:10.1007/s40292-020-00371-4
39. Moxham I. Physics of Invasive Blood Pressure Monitoring. Southern African Journal of Anaesthesia and Analgesia. 2003;9(1):33-38. doi:10.1080/22201173.2003.10872990
40. Mittnacht AJC, Kurki TSO. Arterial pressure monitoring. Monitoring in Anesthesia and Perioperative Care. Published online January 1, 2011:45-56. doi:10.1017/CBO9780511974083.008
41. Sackl-Pietsch E. Continuous non-invasive arterial pressure shows high accuracy in comparison to invasive intra-arterial blood pressure measurement. Medicine 2008. Corpus ID: 30046018. https://www.semanticscholar.org/paper/Continuous-non-invasive-arterial-pressure-shows-in/dde63d9510a7f9b0ff258e9b0cafdf150dfb8dc7
2. Nirmalan M, Dark PM. Broader applications of arterial pressure wave form analysis. Continuing Education in Anaesthesia, Critical Care and Pain. 2014;14(6):285-290. doi:10.1093/BJACEACCP/MKT078
3. Muntner P, Einhorn PT, Cushman WC, et al. The Present and Future Blood Pressure Assessment in Adults in Clinical Practice and Clinic-Based Research JACC Scientific Expert Panel. Published online 2019. doi:10.1016/j.jacc.2018.10.069
4. Anon. Blood pressure goals: How low should you go? Harvard Health Publishing, Harvard Medical School. Published 2019. https://www.health.harvard.edu/mens-health/blood-pressure-goals-how-low-should-you-go
5. Verberk WJ, de Leeuw PW. Accuracy of oscillometric blood pressure monitors for the detection of atrial fibrillation: A systematic review. Expert Rev Med Devices. 2012;9(6):635-640. doi:10.1586/erd.12.46
6. O’brien E, Waeber B, Parati G, Staessen J, Myers MG. Clinical Review Blood Pressure Measuring Devices: Recommendations of the European Society of Hypertension.
7. Egmond J van, Lenders JWM, Weernink E, Thien T. Accuracy and Reproducibility of 30 Devices for Self-Measurement of Arterial Blood Pressure. Am J Hypertens. 1993;6(10):873-879. doi:10.1093/ajh/6.10.873
8. Vischer A, Burkard T. Principles of Blood Pressure Measurement – Current Techniques, Office vs Ambulatory Blood Pressure Measurement.; 2016.
9. Forouzanfar M, Dajani HR, Groza VZ, Bolic M, Rajan S, Batkin I. Oscillometric blood pressure estimation: Past, present, and future. IEEE Rev Biomed Eng. 2015;8:44-63. doi:10.1109/RBME.2015.2434215
10. Balestrieri E, Daponte P, Vito L de, Picariello F, Rapuano S. Oscillometric blood pressure waveform analysis: challenges and developments. IEEE. Published online 2019.
11. Abiri A, Chou EF, Qian C, Rinehart J, Khine M. Intra-beat biomarker for accurate continuous non-invasive blood pressure monitoring. Scientific Reports 2022 12:1. 2022;12(1):1-13. doi:10.1038/s41598-022-19096-6
12. Singh O, Sunkaria RK. Detection of Onset, Systolic Peak and Dicrotic Notch in Arterial Blood Pressure Pulses. Measurement and Control (United Kingdom). 2017;50(7-8):170-176. doi:10.1177/0020294017729958
13. Komine H, Asai Y, Yokoi T, Yoshizawa M. Non-invasive assessment of arterial stiffness using oscillometric blood pressure measurement. Biomed Eng Online. 2012;11. doi:10.1186/1475-925X-11-6
14. Antsiperov VE, Mansurov GK, Danilychev M v., Churikov D v. Non-Invasive Blood Pressure Monitoring with Positionable Three-chamber Pneumatic Sensor. Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019), pages 462-465. Published online 2019:462-465.
15. Secomb TW, Castiglioni P, Don F, et al. Formulas to Explain Popular Oscillometric Blood Pressure Estimation Algorithms. Frontiers in Physiology | www.frontiersin.org. 2019;10:1415. doi:10.3389/fphys.2019.01415
16. Avbelj V. Morphological changes of pressure pulses in oscillometric non-invasive blood pressure measurements. In: 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2014 - Proceedings. IEEE Computer Society; 2014:245-248. doi:10.1109/MIPRO.2014.6859569
17. Lowe A, Oh TH, Stewart R. Screening for Atrial Fibrillation during Automatic Blood Pressure Measurements. IEEE J Transl Eng Health Med. 2018;6. doi:10.1109/JTEHM.2018.2869609
18. Hullender DA, Brown OR. Simulations of blood pressure and identification of atrial fibrillation and arterial stiffness using an extended Kalman filter with oscillometric pulsation measurements. Comput Methods Programs Biomed. 2021;198. doi:10.1016/j.cmpb.2020.105768
19. Segers P, Rietzschel ER, Chirinos JA. How to Measure Arterial Stiffness in Humans. Arterioscler Thromb Vasc Biol. 2020;40:1034-1043. doi:10.1161/ATVBAHA.119.313132/FORMAT/EPUB
20. Jeon A, Ro J, Kim J, Baik S, Jeon G. Simulation of the Blood Pressure Estimation Using the Artery Compliance Model and Pulsation Waveform Model. Journal of Sensor Science and Technology. 2013;22(1):38-43. doi:10.5369/JSST.2013.22.1.38
21. Babbs CF. Oscillometric Measurement of Systolic and Diastolic Blood Pressures Validated in a Physiologic Mathematical Model. Vol 11.; 2012. doi:10.1186/1475-925X-11-56
22. Geddes LA, Baker LE. Principles of Applied Biomedical Instrumentation. Published 1975. Accessed December 10, 2019. https://www.bookdepository.com/Principles-Applied-Biomedical-Instrumentation-L-Geddes/9780471608998
23. Lewis F. “Optimal Estimation with an Introduction to Stochastic Control Theory.” John Wiley & Sons, New York; 1986. Accessed December 10, 2019. https://www.scirp.org/reference/ReferencesPapers.aspx?ReferenceID=132449
24. Dawber TR, Thomas HE, Mcnamara PM. Characteristics of the dicrotic notch of the arterial pulse wave in coronary heart disease. Angiology. 1973;24(4). doi:10.1177/000331977302400407
25. Wood P. Aortic stenosis. Am J Cardiol. 1958;1(5). doi:10.1016/0002-9149(58)90138-3
26. Jain SK, Bhaumik B. An Energy Efficient ECG Signal Processor Detecting Cardiovascular Diseases on Smartphone. IEEE Trans Biomed Circuits Syst. 2017;11(2). doi:10.1109/TBCAS.2016.2592382
27. Garcia D, Pibarot P, Kadem L, Durand LG. Respective impacts of aortic stenosis and systemic hypertension on left ventricular hypertrophy. J Biomech. 2007;40(5). doi:10.1016/j.jbiomech.2006.03.020
28. Luz EJ da S, Schwartz WR, Cámara-Chávez G, Menotti D. ECG-based heartbeat classification for arrhythmia detection: A survey. Comput Methods Programs Biomed. 2016;127. doi:10.1016/j.cmpb.2015.12.008
29. Thakor N v., Zhu YS. Applications of Adaptive Filtering to ECG Analysis: Noise Cancellation and Arrhythmia Detection. IEEE Trans Biomed Eng. 1991;38(8). doi:10.1109/10.83591
30. Chazova IE, Golitsyn SP, Zhernakova J v., et al. Management of patients with arterial hypertension and atrial fibrillation. Systemic Hypertension. 2021;18(3). doi:10.26442/2075082x.2021.3.201077
31. Nattel S. New ideas about atrial fibrillation 50 years on. Nature. 2002;415(6868). doi:10.1038/415219a
32. Mills NL, Miller JJ, Anand A, et al. Increased arterial stiffness in patients with chronic obstructive pulmonary disease: a mechanism for increased cardiovascular risk. Published online 2007. doi:10.1136/thx.2007.083493
33. Sabbah HN, Stein PD. Valve origin of the aortic incisura. Am J Cardiol. 1978;41(1). doi:10.1016/0002-9149(78)90128-5
34. Mark JB. Atlas of Cardiovascular Monitoring. Churchill Livingstone Inc., New York, NY. 1998. ISBN:0-443-08891-8.
35. Judge TP, Kennedy JW. Estimation of aortic regurgitation by diastolic pulse wave analysis. Circulation. 1970;41(4). doi:10.1161/01.CIR.41.4.659
36. Shrotriya A. Analysis of Blood Pressure Waveform for Detection and Diagnosis of Cardiovascular Disorders. Dec. 12, 2021. Libraries Research Commons, University of Texas Arlington, dc.creator.orcid 0000-0002-5423-043X.
37. Jablonski I, Glomb G, Morello R. A Laboratory Set-up for Experimentation with the Cuffless Blood Pressure Measurement. In: IEEE Medical Measurements and Applications, MeMeA 2020 - Conference Proceedings. 2020. doi:10.1109/MeMeA49120.2020.913712
38. Sánchez R, Pessana F, Lev G, et al. Central Blood Pressure Waves Assessment: A Validation Study of Non-invasive Aortic Pressure Measurement in Human Beings. High Blood Pressure and Cardiovascular Prevention. 2020;27(2). doi:10.1007/s40292-020-00371-4
39. Moxham I. Physics of Invasive Blood Pressure Monitoring. Southern African Journal of Anaesthesia and Analgesia. 2003;9(1):33-38. doi:10.1080/22201173.2003.10872990
40. Mittnacht AJC, Kurki TSO. Arterial pressure monitoring. Monitoring in Anesthesia and Perioperative Care. Published online January 1, 2011:45-56. doi:10.1017/CBO9780511974083.008
41. Sackl-Pietsch E. Continuous non-invasive arterial pressure shows high accuracy in comparison to invasive intra-arterial blood pressure measurement. Medicine 2008. Corpus ID: 30046018. https://www.semanticscholar.org/paper/Continuous-non-invasive-arterial-pressure-shows-in/dde63d9510a7f9b0ff258e9b0cafdf150dfb8dc7