MATLAB Tool for Reading MIT ECG Database with Signal Processing Capabilities

This MATLAB program is specifically designed for reading and processing the MIT-BIH ECG database, offering researchers powerful tools for electrocardiogram analysis. The implementation includes core functions for parsing standard WFDB (Waveform Database) format files, handling both header information (.hea) and signal data (.dat) files through optimized I/O operations. Key features include signal preprocessing routines that implement digital filtering techniques for noise reduction, QRS complex detection algorithms using wavelet transforms or Pan-Tompkins methods, and heart rate variability analysis modules. The code structure allows for batch processing of multiple records, with built-in visualization functions for plotting ECG waveforms and annotation displays. Researchers can leverage this tool to extract critical cardiac parameters, perform arrhythmia classification, and analyze signal morphology variations. The program's modular architecture supports customization for specific research needs, including integration with machine learning algorithms for automated ECG interpretation. Academic institutions can utilize this software for teaching cardiovascular physiology and digital signal processing concepts, providing students with hands-on experience in biomedical data analysis. The implementation efficiently handles MIT-BIH database-specific formats using native MATLAB file operations combined with signal processing toolbox functions, ensuring accurate temporal alignment of beat annotations with corresponding waveform data. This makes it an essential resource for cardiac disease research, ECG signal characterization studies, and educational applications in clinical cardiology.