• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.884-894
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• 2011

We proposed a new algorithm for detection of first(S1) and second heart sound(S2). Many researches for detecting primary components and those algorithms have good performance at normal heart sound, but the performance is degraded at abnormal heart sound which is contain murmurs generated by heart disease. Therefore we proposed the S1, S2 detection algorithm using three-order Shannon energy difference. Using S1, S2's character which has large energy difference than murmurs, it is reduced noise and detected S1, S2. According to simulation results, not only normal heart sound but also abnormal heart sound, the proposed algorithm has better performance than former study at abnormal heart sound.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.973-982
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• 2010

In this paper, we proposed the single-channel adaptive noise canceller for the enhancement of heart sound (HS) in the auscultation signal. In case of either normal or emergency, a HS diagnosis is difficult due to the various signal source in the chest. Therefore, the HS enhancement is necessary. The conventional active noise canceller(ANC) has two channel, main signal and reference signal. For signal channel, the reference signal in ANC was generated by the proposed HS analyser and BS-Gate based on the characteristic of HS. This reference signal is suitable to the ANC condition. Experimental data were acquisited from MP36, SS30L in BIOPAC Inc., By the experiment, we confirmed that the proposed single-channel ANC was efficient for HS enhancement. And by the comparison with active linear enhancement, it was validate that the proposed ANC is not affected by the variation of a heartbeat.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.53-59
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• 1989

A new proposed method can separate heart sounds and lung sounds by the realization of adaptive noise canceler using adaptive lattice Wiener filter in contrast to adaptive transversal LMS filter and high pass filter as before. Lung sounds and ECG signal are detected for this purpose, and especially the second heart sounds are reduced by finding T wave location with a T wave seeking algorithm. As a result, for heart sounds reduction It was found that adaptive transversal LMS filter required 100-200's orders, 75-100's orders In adaptive transversal MLMS filter, and only 10-20's orders in adaptive lattice Wiener filter. Adaptive filtering technique has shown greater accuracy than high pass filtering without loss of low frequency component.