Design of a wavelet interpolation filter for enhancement of the ST-segment

A wavelet interpolation filter (WIF) is designed for the removal of motion artifacts in the ST-segment of stress ECGs. The WIF consists of two parts. One part is a wavelet transform that decomposes the stress ECG signal into several frequency bands using a Haar wavelet. The other part is an interpol ation method, such as the spline technique, that is used to enhance the rec onstruction performance of the signal decomposed by the wavelet transform. To evaluate the performance of the WIF, three indices are used: signal-to-n oise ratio (SNR), reconstruction square error (RSE) and standard deviation (SD). The MIT/BIH arrhythmia database, the European ST-T database and the T riangular wave are used for evaluation. A noisy ECG signal, corrupted by mo tion artifacts, is simulated by the addition of two types of random noise t o the original ECG signal. For comparison, three indices for the other meth ods are also computed: mean, median and hard thresholding. The performance of the WIF shows that RSE, SNR and SD are 392.7, 18.3 dB and 2.6, respectiv ely, in the case of a noisy signal with an SNR of 7.1 dB, This result is mu ch better than those for the other methods.