Adaptive filtering in exercise high resolution ECG as applied to the hypertrophic cardiomyopathy

The application of adaptive filtering to ECG signals has been investigated for many years. This study shows that the exercise high resolution ECG (HRE CG) can also be processed successfully in a similar way. Two groups were in cluded consisting of 20 healthy individuals and 24 patients with hypertroph ic cardiomyopathy (HCM), The HRECG parameters for both groups were similar (QRSdur: 107 +/-7 vs 114 +/- 18 ms NS, LAS: 25 +/-8 vs 22 +/-6 ms NS). In t he first step, the HRECG signal was acquired at rest to obtain the averaged reference pattern. The next step was associated with peak exercise in whic h one could calculate short duration averaging (similar to 30 beats) or app ly adaptive filtering in which the exercise component (EC) was extracted. E xercise was performed in the supine position on a bicycle ergometer. The lo ad of 50 W was incremented by 50-W steps in 3-minute intervals and the test was ended by fatigue. Signals were recorded in X, Y, and Z bipolar leads w ith a 20-Hz high pass filter. The short time average QRS duration mostly wa s abbreviated in normal individuals in contrast to HCM patients in which ve ntricular activity prolonged with sensitivity, specificity, and negative an d positive predictive values: 79%, 65%, 73%, and 72%, respectively. The ada ptive recurrent filtration (ARF) after cutoff of the EC at the level of 70 ms (this level is the EC mean value of both groups) showed the following st atistics: 63%, 90%, 88%, and 90%. The Student's t-test as applied to the du ration of EC allowed a statistically significant difference between normals and HCM patients (66 +/-4 vs 71 +/-6 ms, P < 0.0052) and between HCM patie nts with and without ventricular tachyarrhythmia and DS (74<plus/minus>6 vs 69 +/-6 ms, P < 0.046).