ECG Segmentation Using Adaptive Hermite Functions

Description

Electrical activity of the heart can be measured via electrodes placed on the human body resulting in the physiological signal called electrocardiogram (ECG). Each heartbeat contains elementary waves (P,QRS,T), which represent different phases of a cardiac cycle. The main characteristics of these waves such as amplitudes, durations or shapes are of great importance for medical experts. In this article, we develop an ECG delineation algorithm which extracts these features and additionally is able to track subtle variations of the elementary waves. To this end we propose an adaptive signal model based on Hermite functions, which is optimized for each heartbeat.

Period	31 Oct 2017
Event title	Asilomar Conference on Signals, Systems, and Computers
Event type	Conference
Location	United StatesShow on map