Abstract: EKG sensors ((150) are placed on a patient (140) to receive electrocardiogram (EKG) recording signals, which are typically combinations of original signals from different sources, such as pacemaker signals, QRS complex signals, and irregular oscillatory signals that suggest an arrhythmia condition. A computing module (120) uses independent component analysis to separate the recorded EKG signals. The separated signals are displayed to help physicians to analyze heart conditions and to identify probably locations of abnormal heart conditions. At least a portion of the separated signals can be further displayed in a chaos phase space portrait to help detect abnormality in heart conditions.

Abstract: A method and system decomposes a cardiac signal, such as an electrocardiogram (ECG) signal, into components. The components are then usable to assist in the detection of an abnormal heart condition. More particularly, a single lead sensor is used to generate a single lead cardiac signal. The cardiac signal is segmented into a set of cycle segments according to detected heart waveforms. The cycle segments are aligned and used to generate a set of cross-sectional signals. The cross-sectional signals are aligned and presented as inputs to a signal separation process, which separates the cardiac signal into a set of components. The components may be grouped according to predefined criteria. The components or groups may be analyzed or displayed to assist in the detection of an abnormal cardiac signal, which may be indicative of an abnormal heart condition. In one example, the signal separation process is a non-orthogonal transformation method such as independent component analysis (ICA).