Evaluation of cardiac signals using discrete wavelet transform with MATLAB graphical user interface.

Area of Science:

• Biomedical Engineering
• Signal Processing

Background:

• Electrocardiogram (ECG) signal analysis is crucial for diagnosing cardiac conditions.
• Automated processing and classification of ECG signals can improve diagnostic efficiency.

Purpose of the Study:

• To develop a MATLAB-based graphical user interface (GUI) for processing and classifying ECG signals based on heart rate.
• To provide a user-friendly tool for analyzing digitized ECG data.

Main Methods:

• ECG signals were processed using R-peak detection with discrete wavelet transform.
• A Bayes classifier was employed for ECG signal classification.
• A MATLAB GUI was designed to visualize ECG signal plots.

Main Results:

• The system analyzed ECG data from the MIT database.
• 18 patients exhibited normal heart rates, while 9 had abnormal rates.
• Tachycardia was detected in 14.81% and bradycardia in 18.52% of patients.

Conclusions:

• The developed GUI is beneficial for non-technical users in analyzing ECG signals for diagnostics.
• The system shows potential for aiding in the early detection of heart rate abnormalities.
• Future work could involve real-time processing using field-programmable gate arrays (FPGAs).