Abstract
The monitoring and processing of electrocardiogram (ECG) beats have been actively studied in recent years: new lines of research have even been developed to analyze ECG signals using mobile devices. Considering these trends, we proposed a simple and low computing cost algorithm to process and analyze an ECG signal. Our approach is based on the use of linear regression to segment the signal, with the goal of detecting the R point of the ECG wave and later, to separate the signal in periods for detecting P, Q, S, and T peaks. After pre-processing of ECG signal to reduce the noise, the algorithm was able to efficiently detect fiducial points, information that is transcendental for diagnosis of heart conditions using machine learning classifiers. When tested on 260 ECG records, the detection approach performed with a Sensitivity of 97.5% for Q-point and 100% for the rest of ECG peaks. Finally, we validated the robustness of our algorithm by developing an ECG sensor to register and transmit the acquired signals to a mobile device in real time.
Highlights
The electrocardiogram (ECG) signal reflects the electrical activity of the heart observed from the strategic points of the human body and represented by quasi-periodic voltage signal
The QRS complex is the depolarization of the right and left heart ventricles, which is used as a reference point for signal analysis
ECG peak was estimated by Sensitivity, which was calculated as the percentage of ECG records the assessed distance (d) was below the preset threshold (Thr) when combination of detected (T1 ) and where the assessed distance (d) was below the preset threshold (Thr) when combination of detected reference (T2 ) points were compared [22]
Summary
The electrocardiogram (ECG) signal reflects the electrical activity of the heart observed from the strategic points of the human body and represented by quasi-periodic voltage signal. The ECG signal contains essential information about the cardiac pathologies affecting the heart, characterized by five peaks known as fiducial points, which are represented by the letters P, Q, R, S, and T (Figure 1) [1,2]. Detection of each section of the ECG signal is essential for health professionals in screening, diagnosis, and monitoring of several heart conditions [3,4]. From a medical point of view, essential information present in the ECG signal are included in the P wave, the QRS complex, and the T wave. These data include the duration of the PR and QT intervals, and the PR and ST segments.
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