سامانه مدیریت نشریات علمی دانشگاه علوم پزشکی مشهد

Goshvarpour, Atefeh, Goshvarpour, Ateke. (1401). The Impact of Gravitational Stress on Cardiac Dynamics Using Entropy. , 20(2), 72-79. doi: 10.22038/ijmp.2022.56462.1944
Atefeh Goshvarpour; Ateke Goshvarpour. "The Impact of Gravitational Stress on Cardiac Dynamics Using Entropy". , 20, 2, 1401, 72-79. doi: 10.22038/ijmp.2022.56462.1944
Goshvarpour, Atefeh, Goshvarpour, Ateke. (1401). 'The Impact of Gravitational Stress on Cardiac Dynamics Using Entropy', , 20(2), pp. 72-79. doi: 10.22038/ijmp.2022.56462.1944
Goshvarpour, Atefeh, Goshvarpour, Ateke. The Impact of Gravitational Stress on Cardiac Dynamics Using Entropy. , 1401; 20(2): 72-79. doi: 10.22038/ijmp.2022.56462.1944

The Impact of Gravitational Stress on Cardiac Dynamics Using Entropy

Iranian Journal of Medical Physics
مقاله 3، دوره 20، شماره 2، خرداد و تیر 2023، صفحه 72-79    اصل مقاله (1.44 M)
نوع مقاله: Original Paper
شناسه دیجیتال (DOI): 10.22038/ijmp.2022.56462.1944
نویسندگان
Atefeh Goshvarpour1؛ Ateke Goshvarpour* 2
1Department of biomedical engineering, Faculty of electrical engineering, Sahand university of technology, Tabriz, Iran.
2Health Technology Research Center, Imam Reza International University, Mashhad, Razavi Khorasan, Iran.
چکیده
Introduction: Until now, the gravitational stress effect on the time domain and frequency heart parameters has been well-documented. However, cardiac signal dynamics have not been studied adequately under the influence of postural changes. In addition, the effect of body positions on the bio-signals has been investigated only from the aspect of feature extraction and the classification problem has not been considered. Among the physiological signals, the heart rate (HR) becomes an emerging modality that captured the attention of many researchers due to its noninvasive recording and its ability to assess autonomic tone modulation. This study attempted to classify cardiac dynamics concerning postural changes by evaluating different entropy algorithms.
Material and Methods: In this study, the ECG signals of 10 participants (five women and five men with a mean age of 28.7±1.2 years) were designated from the database available at Physionet. First, the RR-intervals of electrocardiograms complying with the Pan-Tomkins procedure were estimated. Second, several entropy measures, including Shannon, log energy, sample, differential, Tsallis, Renyi, and approximate entropy, were calculated while participants were in supine rest, in two rapid head-up tilts, two stand-ups, and two slow head-up tilts. Then, we applied the support vector machine to classify different postures using one group vs. all other remaining groups (OVA) and one body posture vs. the resting supine position (BVR) in a k-fold cross-validation scheme.
Results: Empirical results showed that using the entropy measure in a BVR scheme leads to higher of accuracy rates up to 100%.
Conclusion: This framework opens an avenue of research for different gravitational stress-based conditions in a broad range of applications like disease management, sports, and astronautics.
کلیدواژه‌ها
Posture؛ Electrocardiography؛ Entropy؛ Classification؛ Nonlinear Dynamics
مراجع
  1. Miwa C, Sugiyama Y, Mano T, Matsukawa T, Iwase S, Watanabe T, et al. Effects of aging on cardiovascular responses to gravity-related fluid shift in humans. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences. 2000 Jun 1;55(6):M329-35.
  2. Mukai S, Hayano J. Heart rate and blood pressure variabilities during graded head-up tilt. Journal of Applied Physiology. 1995 Jan 1;78(1):212-6.
  3. Iwase S, Mano T, Watanabe T, Saito M, Kobayashi F. Age-related changes of sympathetic outflow to muscles in humans. Journal of gerontology. 1991 Jan 1;46(1):M1-5.
  4. Miwa C, Mano T, Saito M, Iwase S, Matsukawa T, Sugiyama Y, et al. Ageing reduces sympatho‐suppressive response to head‐out water immersion in humans. Acta physiologica scandinavica. 1996 Aug;158(1):15-20.
  5. Guzzetti S, Piccaluga E, Casati R, Cerutti S, Lombardi F, Pagani M, et al. Sympathetic predominance in essential hypertension: a study employing spectral analysis of heart rate variability. Journal of hypertension. 1988 Sep 1;6(9):711-7.
  6. Pagani M, Malfatto G, Pierini S, Casati R, Masu AM, Poli M, et al. Spectral analysis of heart rate variability in the assessment of autonomic diabetic neuropathy. Journal of the autonomic nervous system. 1988 Aug 1;23(2):143-53.
  7. Pfeifer M. Cardiovascular assessment. In: Dyck PJ, Thomas P, editors. Diabetic neuropathy. 2nd ed. Philadelphia: WB Saunders; 1999; 171-84.
  8. Carnethon MR, Liao D, Evans GW, Cascio WE, Chambless LE, Heiss G. Correlates of the shift in heart rate variability with an active postural change in a healthy population sample: The Atherosclerosis Risk In Communities study. American heart journal. 2002 May 1;143(5):808-13.
  9. Vuksanovic V, Gal V, Kalanj J, Simeunovic S. Effect of posture on heart rate variability spectral measures in children and young adults with heart disease. International journal of cardiology. 2005 May 25;101(2):273-8.
  10. Obata Y, Ruzankin P, Ong QJ, Berkowitz DE, Berger RD, Steppan J, Barodka V. The impact of posture on the cardiac depolarization and repolarization phases of the QT interval in healthy subjects. Journal of Electrocardiology. 2017 Sep 1;50(5):640-5.
  11. De Gregorio C, Lentini C, Grimaldi P, Zagari D, Andò G, Di Bella G, et al. P-wave voltage and peaking on electrocardiogram in patients undergoing head-up tilt testing for history of syncope. European Journal of Internal Medicine. 2014 Apr 1;25(4):383-7.
  12. Ciliberti MA, Santoro F, Di Martino LF, Rinaldi AC, Salvemini G, Cipriani F, et al. Predictive value of very low frequency at spectral analysis among patients with unexplained syncope assessed by head-up tilt testing. Archives of Cardiovascular Diseases. 2018 Feb 1;111(2):95-100.
  13. Hnatkova K, Šišáková M, Smetana P, Toman O, Huster KM, Novotný T, et al. Sex differences in heart rate responses to postural provocations. International journal of cardiology. 2019 Dec 15;297:126-34.
  14. Kumar P, Das AK, Halder S. Time-domain HRV analysis of ECG signal under different body postures. Procedia Computer Science. 2020 Jan 1;167:1705-10.
  15. Pincus SM, Gladstone IM, Ehrenkranz RA. A regularity statistic for medical data analysis. Journal of Clinical Monitoring. 1991 Oct;7(4):335-45.
  16. Nardelli M, Scilingo EP, Valenza G. Refined generalized multivariate multiscale fuzzy entropy: A preliminary study on multichannel physiological complexity during postural changes. In2018 26th European Signal Processing Conference (EUSIPCO). 2018; 291-5.
  17. Rawal K, Sethi G. HRV analysis of different postures of young healthy women using signal processing methods. Biomedical Engineering: Applications, Basis and Communications. 2021 Feb 30;33(01):2150006.
  18. Byun S, Kim AY, Jang EH, Kim S, Choi KW, Yu HY, et al. Entropy analysis of heart rate variability and its application to recognize major depressive disorder: A pilot study. Technology and Health Care. 2019 Jan 1;27(S1):407-24.
  19. Kang J, Chen H, Li X, Li X. EEG entropy analysis in autistic children. Journal of Clinical Neuroscience. 2019 Apr 1;62:199-206.
  20. Wang F, Wang H, Fu R. Real-time ECG-based detection of fatigue driving using sample entropy. Entropy. 2018 Mar 15;20(3):196.
  21. Horie T, Burioka N, Amisaki T, Shimizu E. Sample entropy in electrocardiogram during atrial fibrillation. Yonago Acta Medica. 2018;61(1):049-57.
  22. Xue SW, Yu Q, Guo Y, Song D, Wang Z. Resting-state brain entropy in schizophrenia. Comprehensive Psychiatry. 2019 Feb 1;89:16-21.
  23. Acharya UR, Hagiwara Y, Koh JE, Oh SL, Tan JH, Adam M, et al. Entropies for automated detection of coronary artery disease using ECG signals: A review. Biocybernetics and Biomedical Engineering. 2018 Jan 1;38(2):373-84.
  24. Molina V, Bachiller A, Gomez-Pilar J, Lubeiro A, Hornero R, Cea-Cañas B, et al. Deficit of entropy modulation of the EEG in schizophrenia associated to cognitive performance and symptoms. A replication study. Schizophrenia Research. 2018 May 1;195:334-42.
  25. Thul A, Lechinger J, Donis J, Michitsch G, Pichler G, Kochs EF, et al. EEG entropy measures indicate decrease of cortical information processing in Disorders of Consciousness. Clinical Neurophysiology. 2016 Feb 1;127(2):1419-27.
  26. Eckmann JP, Ruelle D. Fundamental limitations for estimating dimensions and Lyapunov exponents in dynamical systems. Physica D: Nonlinear Phenomena. 1992 May 1;56(2-3):185-7.
  27. Bolea J, Laguna P, Remartínez JM, Rovira E, Navarro A, Bailón R. Methodological framework for estimating the correlation dimension in HRV signals. Computational and mathematical methods in medicine. 2014 Jan 1;2014.
  28. Heldt T, Oefinger MB, Hoshiyama M, Mark RG. Circulatory response to passive and active changes in posture. InComputers in Cardiology. 2003; 263-6.
  29. Pincus SM. Approximate entropy as a measure of system complexity. Proceedings of the National Academy of Sciences. 1991 Mar 15;88(6):2297-301.
  30. Rutanen K. Tim matlab 1.2.0.  Matlab toolbox. 2011; Available at: https://www.cs.tut.fi/~timhome/tim/tim/matlab/directory.htm
 

 

 

 

 

آمار
تعداد مشاهده مقاله: 289
تعداد دریافت فایل اصل مقاله: 204