Computationally inexpensive methods for intra-cardiac atrial bipolar electrogram compression

This paper reports studies of mathematical algorithms for intra-cardiac atrial bipolar electrogram compression suitable with implementation on implantable devices.

Bipolar intra-cardiac electrograms (IEGMs) of high right atrium were obtained from 20 patients who underwent electrophysiological studies for arrhythmias. Four thousand seven hundred and eighty-two seconds of IEGM were collected and divided into three rhythm groups: sinus rhythm (SR), atrial fibrillation (AF) and atrial flutter (AFL). Since mathematical algorithms suitable for use with implantable devices demand low computational cost, we employed piecemeal linear approximation methods (ZOP--Zero Order Prediction and SAPA--Scan Along Polygonal Approximation), and beat detection method (Peak) both or which need small numbers of operations to perform electrogram compression. Compression ratio (CR) and percent root mean square difference (PRD) were used to compare the three methods, with statistical analyses performed using paired t-test.

The best performance was obtained using the Peak method which reaches an average CR of 10.6 in the case of SR group, 2.8 for AF, and 3.6 for AFL groups, respectively, while PRD lies below 2% for SR and AFL groups and 6% for the AF group. Results show that, for bipolar electrograms, the Peak method reaches statistically significant better performance (P<0.001) in all cases except for Peak vs SAPA applied to AF (P=0.2). The number of operations necessary to compress the data indicate that time consumption can be reduced to be suitable for real time compression in implantable devices. The Peak method, which was assumed to receive the instant of occurrence of each recognized beat, from the hardware of the device, requires fewer operations than ZOP and SAPA. Increasing the length of electrograms recorded in pacemakers will enhance the amount of information provided by the implantable device, allowing more detailed characterization of the intra-cardiac activity and leading to new perspectives in arrhythmia diagnosis and therapy.