ECG-Based Blood Pressure Estimation Using Mechano-Electric Coupling Concept
Seyedeh Somayyeh Mousavi, Mostafa Charmi, Mohammad Firouzmand,, Mohammad Hemmati, Maryam Moghadam, Yadollah Ghorbani

TL;DR
This study introduces a novel ECG-based method for continuous, noninvasive blood pressure estimation using only the ECG signal and machine learning, achieving clinically acceptable accuracy levels.
Contribution
The paper proposes a new ECG-only blood pressure estimation technique utilizing whole-based feature vectors and adaptive boosting regression, demonstrating compliance with medical standards.
Findings
Achieves A grade for diastolic and mean arterial pressure estimation.
Attains B grade for systolic blood pressure estimation.
Estimates blood pressure noninvasively without cuffs or calibration.
Abstract
The Electrocardiograph signal represents the heart's electrical activity while blood pressure results from the heart's mechanical activity. Previous studies have investigated how the heart's electrical and mechanical activities are related and have referred to their relationship as the Mechano-Electric Coupling term. A new method to estimate the blood pressure including is proposed which uses only the Electrocardiograph signal. In spite of studies performed on feature extraction based on the signals' physiological parameters (Parameter-based), in this work, the feature vectors are formed with samples of the Electrocardiograph signal in a particular time frame (Whole-based) and these vectors are input into Adaptive Boosting Regression to estimate blood pressure. The nonlinear relationship which correlates blood pressure with the Electrocardiograph signal is concluded by the results of…
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