Methods of Blood Pressure Estimation Using Deep Learning : A Review

Authors

  • Praneeta Grace. M  PG Scholar, Department of Biomedical Instrumentation Engineering, School of Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.

Keywords:

Methods of Blood Pressure Estimation Using Deep Learning : A Review

Abstract

This paper presents a review of different deep learning methods used in blood pressure estimation. The recent technique adopted the cuff-less method for blood pressure estimation. One of the common cuff-less methods uses the correlation between Pulse Wave Velocity (PWV) and ECG. But these methods do have some limitations, such as the necessity for periodic calibration as PWV and ECG varies from person to person. With the advent of Deep Learning, many new techniques are used for the estimation of BP. The VGGNet and CNN have automatics feature extraction and learning ability. Thus, these two techniques are found to be the best among all the techniques.

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International Journal of Scientific Research in Science and Technology

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Published

2020-03-05

Issue

Volume 5, Issue 5, March-April-2020

Section

Research Articles

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How to Cite

[1]
Praneeta Grace. M, " Methods of Blood Pressure Estimation Using Deep Learning : A Review, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 5, Issue 5, pp.17-27, March-April-2020.