Вопросы радиоэлектроники. 2019; : 70-76
Оценка артериального давления по данным плетизмографии
https://doi.org/10.21778/2218-5453-2019-10-70-76Аннотация
Мониторинг непрерывного артериального давления важен для профилактики и ранней диагностики сердечно-сосудистых заболеваний, число которых растет во всем мире. Измерение артериального давления (АД) на основе сигнала плетизмографии является одним из многих простых методов неинвазивного контроля кровяного давления. В статье представлен сравнительный анализ сигналов АД и плетизмограмм (ПГ), синхронизированных во времени, а также их спектральных особенностей. Выявлено определенное временное структурное сходство сигналов АД и ПГ (соответствие временных интервалов, амплитуд) при одновременном сдвиге во времени сигнала ПГ. Показано, насколько адекватно можно судить об АД, имея только снятые данные ПГ. В качестве временных интервалов выбиралась минутная последовательность сердечных циклов. Отмечается, что при соответствующей калибровке сигналов ПГ возможна оценка среднего значения АД за несколько сердечных циклов. Полученные результаты в дальнейшем могут быть использованы в диагностике различных патологий.
Список литературы
1. Chobanian A. V., Bakris G. L., Black H. R., et al. The national high blood pressure education program coordinating committee. Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure // Hypertension. 2003. No. 42 (6). P. 1206–1252.
2. Choi Y., Zhang Q., Ko S. Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert–Huang transform // Comput. Electr. Eng. 2013. No. 39 (1). P. 103–111.
3. Peňáz J. Photoelectric measurement of blood pressure, volume and flow in the finger // Digest of the 10th International Conference on Medical and Biological Engineering. Dresden, 1973. 104 p.
4. Wang J.-J., Liu S.-H., et al. Development of an arterial applanation tonometer for detecting arterial blood pressure and volume // Biomedical Engineering – Applications, Basis & Communications. 2004. No. 16 (6). P. 322–330.
5. Williams B., Lacy P. S., et al. Development and validation of a novel method to derive central aortic systolic pressure from the radial pressure waveform using an n-point moving average method // J. Am. Coll. Cardiol. 2011. No. 57 (8). P. 951–961.
6. Nair D., Tan S.-Y., Gan H.-W., et al. The use of ambulatory tonometric radial arterial wave capture to measure ambulatory blood pressure: the validation of a novel wrist-bound device in adults // Journal of Human Hypertension. 2008. No. 22. P. 220–222.
7. Liu M., Po L-M., Fu H. Cuffless blood pressure estimation based on photoplethysmography signal and its second derivative [Электронный ресурс]. URL: www.ee.cityu.edu.hk/~lmpo/publications/2016_PPG_Blood_Pressure.pdf (дата обращения: 16.05.2019).
8. Slapnicar G., Lustrek M. Continuous blood pressure estimation from PPG signal // Informatica. 2018. No. 42. P. 33–42.
9. Pielmuş A-G., Osterland D., Klum M., et al. Correlation of arterial blood pressure to synchronous piezo, impedance and photoplethysmographic signal features // Current Directions in Biomedical Engineering. 2017. No. 3 (2). P. 749–753.
10. Song S. H., Cho J. S., Oh H. S., et al. Estimation of blood pressure using Plethysmography on the wrist // 36th Annual Computers in Cardiology Conference (CinC). 2009. P. 741–744.
11. Taha Z., Shirley L., Razman M. A review on non-invasive hypertension monitoring system by using photoplethysmography method // Movement, Health & Exercise. 2017. No. 6 (1). P. 47–57.
12. Khalid S. G., Zhang J., Chen F., et al. Blood pressure estimation using photoplethysmography only: comparison between different machine learning approaches // Journal of Healthcare Engineering. 2018. P. 1–13.
13. Millasseau S. C., Guigui F. G., Kelly R. P., et al. Noninvasive assessment of the digital volume pulse. Comparison with the peripheral pressure pulse // Hypertension. 2000. No. 36 (6). P. 952–956.
14. PhysioBank ATM – PhysioNet [Электронный ресурс]. URL: http://www.physionet.org/cgi-bin/atm/ATM (дата обращения: 16.05.2018).
Issues of radio electronics. 2019; : 70-76
Estimation of arterial pressure from pletismography data
https://doi.org/10.21778/2218-5453-2019-10-70-76Abstract
Continuous blood pressure monitoring is important for the prevention and early diagnosis of cardiovascular diseases, the number of which is growing worldwide. A method for measuring blood pressure (BP) based on a plethysmography signal is one of many simple methods for non-invasive monitoring of blood pressure. The article presents a comparative analysis of blood pressure signals and plethysmograms (PG) synchronized in time, as well as their spectral features. A certain temporal structural similarity of the BP and PG signals (correspondence of time intervals, amplitudes) with a simultaneous time shift of the PG signal was revealed. It is shown how adequately one can judge blood pressure, having only the captured PG data. As the time intervals, the minute sequence of cardiac cycles was chosen. It is noted that with appropriate calibration of PG signals, it is possible to estimate the average blood pressure value for several cardiac cycles. The results obtained can be used in the diagnosis of various pathologies.
References
1. Chobanian A. V., Bakris G. L., Black H. R., et al. The national high blood pressure education program coordinating committee. Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure // Hypertension. 2003. No. 42 (6). P. 1206–1252.
2. Choi Y., Zhang Q., Ko S. Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert–Huang transform // Comput. Electr. Eng. 2013. No. 39 (1). P. 103–111.
3. Peňáz J. Photoelectric measurement of blood pressure, volume and flow in the finger // Digest of the 10th International Conference on Medical and Biological Engineering. Dresden, 1973. 104 p.
4. Wang J.-J., Liu S.-H., et al. Development of an arterial applanation tonometer for detecting arterial blood pressure and volume // Biomedical Engineering – Applications, Basis & Communications. 2004. No. 16 (6). P. 322–330.
5. Williams B., Lacy P. S., et al. Development and validation of a novel method to derive central aortic systolic pressure from the radial pressure waveform using an n-point moving average method // J. Am. Coll. Cardiol. 2011. No. 57 (8). P. 951–961.
6. Nair D., Tan S.-Y., Gan H.-W., et al. The use of ambulatory tonometric radial arterial wave capture to measure ambulatory blood pressure: the validation of a novel wrist-bound device in adults // Journal of Human Hypertension. 2008. No. 22. P. 220–222.
7. Liu M., Po L-M., Fu H. Cuffless blood pressure estimation based on photoplethysmography signal and its second derivative [Elektronnyi resurs]. URL: www.ee.cityu.edu.hk/~lmpo/publications/2016_PPG_Blood_Pressure.pdf (data obrashcheniya: 16.05.2019).
8. Slapnicar G., Lustrek M. Continuous blood pressure estimation from PPG signal // Informatica. 2018. No. 42. P. 33–42.
9. Pielmuş A-G., Osterland D., Klum M., et al. Correlation of arterial blood pressure to synchronous piezo, impedance and photoplethysmographic signal features // Current Directions in Biomedical Engineering. 2017. No. 3 (2). P. 749–753.
10. Song S. H., Cho J. S., Oh H. S., et al. Estimation of blood pressure using Plethysmography on the wrist // 36th Annual Computers in Cardiology Conference (CinC). 2009. P. 741–744.
11. Taha Z., Shirley L., Razman M. A review on non-invasive hypertension monitoring system by using photoplethysmography method // Movement, Health & Exercise. 2017. No. 6 (1). P. 47–57.
12. Khalid S. G., Zhang J., Chen F., et al. Blood pressure estimation using photoplethysmography only: comparison between different machine learning approaches // Journal of Healthcare Engineering. 2018. P. 1–13.
13. Millasseau S. C., Guigui F. G., Kelly R. P., et al. Noninvasive assessment of the digital volume pulse. Comparison with the peripheral pressure pulse // Hypertension. 2000. No. 36 (6). P. 952–956.
14. PhysioBank ATM – PhysioNet [Elektronnyi resurs]. URL: http://www.physionet.org/cgi-bin/atm/ATM (data obrashcheniya: 16.05.2018).
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