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Application of a wavelet adaptive filter to minimise distortion of the ST-segment

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Abstract

A wavelet adaptive filter (WAF) for the removal of baseline wandering in ECG signals is described. The WAF consists of two parts. The first part is a wavelet transform that decomposes the ECG signal into seven frequency bands using Vaidyanathan-Hoang wavelets. The second part is an adaptive filter that uses the signal of the seventh lowest-frequency band among the wavelet transformed signals as primary input and a constant as reference input. To evaluate the performance of the WAF, two baseline wandering elimination filters are used, a commercial standard filter with a cutoff frequency of 0.5 Hz and a general adaptive filter. The MIT/BIH database and the European ST-T database are used for the evaluation. The WAF performs better in the average power of eliminated noise than the standard filter and adaptive filter. Furthermore, it shows a lower ST-segment distortion than the standard filter and the adaptive filter.

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Authors and Affiliations

  1. Department of Biomedical Engineering, College of Health Science and Research Institute of Medical Engineering, Yonsei University, 234, Maeji-Ri, Heungup-Myon, 222-701, Wonju City, Kangwon Do, Korea

    K. L. Park,  K. J. Lee & H. R. Yoon

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  1. K. L. Park
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  2. K. J. Lee
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  3. H. R. Yoon
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Correspondence to K. J. Lee.

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Park, K.L., Lee, K.J. & Yoon, H.R. Application of a wavelet adaptive filter to minimise distortion of the ST-segment. Med. Biol. Eng. Comput. 36, 581–586 (1998). https://doi.org/10.1007/BF02524427

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  • DOI: https://doi.org/10.1007/BF02524427

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