Amark: Automated Marking and Processing Techniques for Ambulatory ECG Data

TL;DR

This paper introduces Amark, a MATLAB-based software tool that automates ECG data processing, including noise filtering, beat identification, and heart rate variability analysis, validated on standard databases.

Contribution

Amark provides an automated, end-to-end solution for ambulatory ECG processing, combining beat detection, noise filtering, and variability analysis, with validation on established datasets.

Findings

Effective noise filtering and beat detection demonstrated on MIT-BIH databases

Accurate classification and noise detection results

Facilitates reliable heart rate variability analysis

Abstract

We describe techniques and specifications of MATLAB software to process ambulatory electrocardiogram (ECG) data. Through template-based beat identification and simple pattern recognition models on the intervals between regular heart beats, we filter noisy sections of waveform and ectopic beats. Our end-to-end process can be used towards analysis of ECG and calculation of heart rate variability metrics after beat adjustments, removals and interpolation. Classification and noise detection is assessed on the human-annotated MIT-BIH Arrythmia and Noise Stress Test Databases.