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Adaptive P-end Detection

IP.com Disclosure Number: IPCOM000241136D
Publication Date: 2015-Mar-30
Document File: 7 page(s) / 3M

Publishing Venue

The IP.com Prior Art Database

Abstract

Reliable analysis of the electrocardiogram (ECG) of the patient is required for detecting arrhythmias of the human heart. In typical state of the art implantable medical devices (IMDs) for therapy of cardiac diseases, as e.g. cardiac pacemakers or implantable cardiac defibrillators (ICDs), the ECG of the patient is recorded and automatically evaluated via specific computing algorithms implemented within the signal processing unit of the cardiac pacemaker.

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Adaptive P-end Detection

Reliable analysis of the electrocardiogram (ECG) of the patient is required for detecting arrhyth- mias of the human heart. In typical state of the art implantable medical devices (IMDs) for therapy of cardiac diseases, as e.g. cardiac pacemakers or implantable cardiac defibrillators (ICDs), the ECG of the patient is recorded and automatically evalu- ated via specific computing algorithms imple- mented within the signal processing unit of the cardiac pacemaker.

The most distinctive signal parts of a physiologi- cal ECG are the P-wave (represents atrial depolar- ization), the QRS-complex (represents ventricular contraction) and the T-wave (represents ventricu- lar repolarization). Most common automatic ECG detection algorithms are targeted on identification of these signal parts, wherein research is continu- ally performed in science in order to develop new strategies for optimization of such algorithms.

In automatic ECG detection, important param- eters are onsets/offsets of a wave e.g. for calculat- ing the lengths of signal intervals. Among others, it is particularly required to detect the end of the P-wave as precisely as possible in order to com- pute a PR-interval which can be associated with various medical conditions.

Most known P-end detection algorithms are based on filtering or adaptive thresholding, where P-end is declared when the P-wave amplitude is below a threshold value, or when the P-wave slope is smaller than another threshold value. More advanced algorithms have also been proposed for delineation of P, QRS, and T waves, e.g., based on wavelet transform, multi-scale morphological derivative transform, empirical mode decomposi- tion, etc.

The main drawback of the filtering-based approach is that frequency variations in the char- acteristic waves often adversely affect its perfor- mance. The frequency distribution of P-wave, QRS complex, and T wave generally overlaps with that of the noise, resulting in both false positive and false negative detections. The main draw- backs of conventional thresholding techniques are their high sensitivity to noise and their low effi- ciency when dealing with varying morphologies.

Although more accurate P-end detection can be achieved by using more advanced signal process- ing techniques, the associated algorithm com- plexity and computational cost make them not suitable for real-time processing in embedded sys- tems, such as the battery-powered IMDs, as car- diac pacemakers and ICDs.

In the following, a novel apparatus and method for real-time detection of the end of a P-wave in an ECG using IMDs is presented. The proposed method and apparatus allows accurate and reli- able detection of the end of P-wave in an ECG, intracardiac electrogram (IEGM), surface ECG, or subcutaneous ECG in real time. Alternatively, the algorithm can also be applied for detection of P-wave onset, as well as the onset/offset of QRS complex, and the onset/offset of T wave. Several...