Full Paper View Go Back

LabVIEW based detection of Pulse Transit Time from Plethysmogram and ECG signals for estimation of Blood Pressure

Alister Dsouza1 , M.S. Panse2

  1. Dept. Electrical Engineering, VJTI, Mumbai, India.
  2. Dept. Electrical Engineering, VJTI, Mumbai, India.

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.4 , pp.36-40, Aug-2017


Online published on Aug 30, 2017


Copyright © Alister Dsouza, M.S. Panse . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library


XML View     PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Alister Dsouza, M.S. Panse, “LabVIEW based detection of Pulse Transit Time from Plethysmogram and ECG signals for estimation of Blood Pressure,” International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.4, pp.36-40, 2017.

MLA Style Citation: Alister Dsouza, M.S. Panse "LabVIEW based detection of Pulse Transit Time from Plethysmogram and ECG signals for estimation of Blood Pressure." International Journal of Scientific Research in Computer Science and Engineering 5.4 (2017): 36-40.

APA Style Citation: Alister Dsouza, M.S. Panse, (2017). LabVIEW based detection of Pulse Transit Time from Plethysmogram and ECG signals for estimation of Blood Pressure. International Journal of Scientific Research in Computer Science and Engineering, 5(4), 36-40.

BibTex Style Citation:
@article{Dsouza_2017,
author = {Alister Dsouza, M.S. Panse},
title = {LabVIEW based detection of Pulse Transit Time from Plethysmogram and ECG signals for estimation of Blood Pressure},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {8 2017},
volume = {5},
Issue = {4},
month = {8},
year = {2017},
issn = {2347-2693},
pages = {36-40},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=435},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=435
TI - LabVIEW based detection of Pulse Transit Time from Plethysmogram and ECG signals for estimation of Blood Pressure
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Alister Dsouza, M.S. Panse
PY - 2017
DA - 2017/08/30
PB - IJCSE, Indore, INDIA
SP - 36-40
IS - 4
VL - 5
SN - 2347-2693
ER -

620 Views    314 Downloads    214 Downloads
  
  

Abstract :
Blood Pressure is the pressure exerted by blood on the walls of arteries. Normal blood pressure is considered to be a systolic blood pressure of 120 millimetres of mercury and diastolic pressure of 80 millimetres of mercury (stated as "120 over 80"). If an individual were to have a consistent blood pressure reading of 140 over 90, he would be evaluated for having high blood pressure. If left untreated, high blood pressure can damage important organs, such as the brain and kidneys, as well as lead to a stroke. Thus it becomes important to measure blood pressure as it can lead to early diagnosis of diseases that may be linked to high or low blood pressure. PTT is the time taken by the arterial pulse propagating from the heart to a peripheral site. This can be calculated from ECG signals and PlethysmoGram signals. Since, PTT has been found to be correlated to Blood Pressure, it is imperative to calculate PTT accurately. In this paper, algorithms used to calculate the points of interest in the ECG signal and the signal along with the calculation of PTT from them is developed. The coding has been done in LabVIEW which is has a graphical programming syntax that makes it simple to visualize, create, and code engineering systems.

Key-Words / Index Term :
Blood Pressure, ECG,PTT,PPG, LabVIEW

References :
[1] Ding, X., Zhang, Y., Liu, J., Dai, W. and Tsang, H. (2016). Continuous Cuffless Blood Pressure Estimation Using Pulse Transit Time and Photoplethysmogram Intensity Ratio. IEEE Transactions on Biomedical Engineering, 63(5), pp.964-972.
[2] Gesche, H., Grosskurth, D., KĂĽchler, G. and Patzak, A. (2011). Continuous blood pressure measurement by using the pulse transit time: comparison to a cuff-based method. European Journal of Applied Physiology, 112(1), pp.309-315.
[3] Kounalakis, S. and Geladas, N. (2009). The Role of Pulse Transit Time as an Index of Arterial Stiffness During Exercise. Cardiovascular Engineering, 9(3), pp.92-97.
[4] HALLOCK, P. (1934). ARTERIAL ELASTICITY IN MAN IN RELATION TO AGE AS EVALUATED BY THE PULSE WAVE VELOCITY METHOD. Archives of Internal Medicine, 54(5), p.770.
[5] Smith, R., Argod, J., Pepin, J. and Levy, P. (1999). Pulse transit time: an appraisal of potential clinical applications. Thorax, 54(5), pp.452-457.
[6] OCHIAI R, TAKEDA J, HOSAKA H, SUGO Y, TANAKA R, SOMA T: The relationship between modified pulse wave transit time and cardiovascular changes in isoflurane anesthetized dogs. J ClinMonitComput 15: 493-501, 1999.
[7] AHLSTROM C, JOHANSSON A, UHLIN F, LĂ„NNE T, ASK P: Noninvasive investigation of blood pressure changes using the pulse wave transit time: a novel approach in the monitoring of hemodialysis patients. J Artif Organs 8: 192-197, 2005.
[8] S. Alty, N. Angarita-Jaimes, S. Millasseau and P. Chowienczyk, "Predicting Arterial Stiffness From the Digital Volume Pulse Waveform", IEEE Transactions on Biomedical Engineering, vol. 54, no. 12, pp. 2268-2275, 2007.
[9] Fechir M, Schlereth T, Purat T, Kritzmann S, Geber C, Eberle T, Gamer M, Birklein F: patterns of sympathetic responses induced by different stress tasks. openneurol j 2: 25-31, 2008.
[10] Schmalgemeier H, Bitter T, Bartsch S, Bullert K, Fischbach T, Eckert S, Horstkotte D, Oldenburg O: pulse transit time: validation of blood pressure measurement under positive airway pressure ventilation. sleep breath 16: 1105-1112, 2012.
[11] Contal O, Carnevale C, Borel J-C, Sabil A, Tamisier R, LĂ©vy P, Janssens J-P, PĂ©pin J-L: pulse transit time as a measure of respiratory effort under non-invasive ventilation. eurrespir j 41: 346-353, 2013.
[12] KortekaasMc, NiehofSp, Van VelzenMhn, Galvin Em, HuygenFjpm, StolkerRj: pulse transit time as a quick predictor of a successful axillary brachial plexus block. ActaAnaesthesiolScand 56: 1228-1233, 2012.
[13] Ma, H. (2014). A Blood Pressure Monitoring Method for Stroke Management. BioMed Research International, 2014, pp.1-7.
[14] Zhang, G., Liu, C., Ji, L., Yang, J. and Liu, C. (2016). Effect of a Percutaneous Coronary Intervention Procedure on Heart Rate Variability and Pulse Transit Time Variability: A Comparison Study Based on Fuzzy Measure Entropy. Entropy, 18(7), p.246.
[15] Gómez García, M., Troncoso Acevedo, M., Rodriguez Guzmán, M., Alegre de Montaner, R., FernándezFernández, B., del Río Camacho, G. and González-Mangado, N. (2014). Can Pulse Transit Time Be Useful for Detecting Hypertension in Patients in a Sleep Unit?.Archivos de Bronconeumología (English Edition), 50(7), pp.278-284.
[16] Ding, X., Zhang, Y. and Tsang, H. (2016). Impact of heart disease and calibration interval on accuracy of pulse transit time–based blood pressure estimation. Physiological Measurement, 37(2), pp.227-237.
[17] T. Wibmer, et al., "Pulse transit time and blood pressure during cardiopulmonary exercise tests," Physiol. Res., vol. 63, pp. 287-296, 2014.

Authorization Required

 

You do not have rights to view the full text article.
Please contact administration for subscription to Journal or individual article.
Mail us at  support@isroset.org or view contact page for more details.

Go to Navigation