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KMID : 0372919950160040517
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Journal of Biomedical Engineering Research
1995 Volume.16 No. 4 p.517 ~ p.524
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Design of a Cascade Adaptive Filter for the Performance sn Detection of Segment
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Abstract
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This paper is a study on the design of the cascade adaptive filter (CAF) for baseline wandering elimination in order to enhance the performance of the detection of ST segments in ECG. The CAF using Least Mean Square (LMS) algorithm consists of two filters. The primary adaptive filter which has the cutoff frequency of 0.3Hz eliminates the baseline wandering in raw ECG The secondary adaptive filter removes the remnant baseline wandering which is not eliminated by the primary adaptive filter. The performance of the CAF was compared with the standard filter, the recursive filter, and the adaptive impulse correlated Hlter (AICF). As a result, the CAF showed a lower signal distortion than the standard filter and the AICF Also, the CAF showed a better perf’’’’ormance in noise elimination than the standard filter and the recursive filter. In conclusion, considering the characteristics of the noise elimination and the signal distortion, the CAF shows a better performance in the removal of the baseline wandering than the other three Otters and suggests the high performance in the detection of ST segment.
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