Biomedical Signal Processing: An ECG Application

Abstract

The electrocardiogram (ECG) is a low-cost non-invasive sensor that measures conduction through the heart. By interpreting the morphology of a person’s ECG, clinical domain experts are able to infer the functionality of the underlying heartbeat, and diagnose irregularities. Moreover, a variety of signal processing algorithms have been developed to automatically monitor ECG recordings for patients and clinicians, both in and out of the clinical setting. The periodic nature of the ECG makes it particularly suitable for frequency-based analysis. Wavelet analysis, which uses brief oscillators to extract information from different portions of the signals, has proven highly effective. This chapter demonstrates the application of the continuous wavelet transform on multi-channel ECG signals from patients with arrhythmias. The information extracted is used to develop a high-performing heartbeat classifier that can distinguish between various types of regular and irregular beats.