README: ECG Signal Analysis MATLAB Script Overview This MATLAB script is designed to analyze ECG data from PhysioNet databases (https://drive.google.com/drive/folders/1r4cgBXT63XsNcLTBYUu0NfStxiLZeT7A?usp=sharing) or any compatible .mat file. It is optimized for ECG signals sampled at 128 Hz but can handle other sample rates with appropriate adjustments to the script. Analysis Criteria Detect R-peaks using signal processing techniques. Extract individual cardiac waveforms. Calculate diagnostic features: wave amplitudes, durations, and time intervals. Generate a comprehensive table of metrics with classifications of abnormalities. Evaluate deviations from healthy ranges and classify findings as Benign or Pathological.

Key Features Interactive Workflow: User prompts for file input, graph selection, and optional visualizations. Visualization: Plots the filtered ECG signal with detected R-peaks. Displays extracted cardiac cycles and overlays the mean waveform. Efficiency: Optimized for matrix operations for fast processing of large datasets. Interpretability: Generates a clear diagnostic table of recorded metrics, healthy ranges, and classifications. Optionally explains the clinical significance of each metric for user interpretation. Flexibility: Allows users to analyze multiple ECG files or graphs without restarting the script.

Signal Processing Pipeline

Filtering and R-Wave Detection

Uses a high-pass FIR filter to remove low-frequency noise. Detects R-peaks with the findpeaks() function. Accounts for both positive and negative polarity ECG signals. Wave Component Identification

P wave: Detected using findpeaks() within a restricted backward range. Q wave: Located by finding the minimum value in a restricted range before the R-peak. S wave: Located by finding the minimum value in a restricted range after the R-peak. T wave: Detected using findpeaks() in a restricted forward range. Feature Extraction

Calculates key diagnostic features using matrix operations and sliding windows for efficiency. Extracts the following metrics: Intervals: PR, QT, RR, ST Segments Amplitudes: P, Q, R, S, T waves Durations: QRS width, P wave width, S wave width Abnormality Evaluation

Evaluates deviations of recorded metrics from predefined healthy ranges. Normalizes deviations to account for the range of each metric. Classifies findings as: Normal Abnormal Benign (High/Low) Abnormal Pathological (High/Low) Diagnostics

Summarizes the results in a diagnostic table. Highlights the most abnormal metric. Provides an overall diagnosis based on thresholds, such as: Tachycardia with Arrhythmia Bradycardia Bundle Branch Block Acute Myocardial Infarction