Adaptive Filtering for Baseline Wander Noise of ECG Using Neural Networks

Juwon LEE; Weonrae JO; Gunki LEE

Adaptive Filtering for Baseline Wander Noise of ECG Using Neural Networks

Juwon LEE, Weonrae JO, Gunki LEE

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This study proposed the new method to minimize distortion of the ST segment and noise deletion of ECG baseline wander. In general, the standard filter and adaptive filter are used to remove the baseline wander of the ECG. The standard filter, however, is limited because the frequency of the baseline signal is variable and the baseline wander's spectrum overlaps with the ST segment's spectrum, and for the adaptive filter, it is difficult to select the reference signal. This study proposed a new, structured adaptive filter that is to remove noise without reference signal using neural networks. In order to confirm performance, this paper used ECG data of MIT-BIHs and obtained significant results through the tests.

Publication: IEICE TRANSACTIONS on Information Vol.E87-D No.1 pp.261-266

Publication Date: 2004/01/01

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Type of Manuscript: LETTER

Category: Medical Engineering

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Juwon LEE, Weonrae JO, Gunki LEE, "Adaptive Filtering for Baseline Wander Noise of ECG Using Neural Networks" in IEICE TRANSACTIONS on Information, vol. E87-D, no. 1, pp. 261-266, January 2004, doi: .
Abstract: This study proposed the new method to minimize distortion of the ST segment and noise deletion of ECG baseline wander. In general, the standard filter and adaptive filter are used to remove the baseline wander of the ECG. The standard filter, however, is limited because the frequency of the baseline signal is variable and the baseline wander's spectrum overlaps with the ST segment's spectrum, and for the adaptive filter, it is difficult to select the reference signal. This study proposed a new, structured adaptive filter that is to remove noise without reference signal using neural networks. In order to confirm performance, this paper used ECG data of MIT-BIHs and obtained significant results through the tests.
URL: https://globals.ieice.org/en_transactions/information/10.1587/e87-d_1_261/_p

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@ARTICLE{e87-d_1_261,
author={Juwon LEE, Weonrae JO, Gunki LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Adaptive Filtering for Baseline Wander Noise of ECG Using Neural Networks},
year={2004},
volume={E87-D},
number={1},
pages={261-266},
abstract={This study proposed the new method to minimize distortion of the ST segment and noise deletion of ECG baseline wander. In general, the standard filter and adaptive filter are used to remove the baseline wander of the ECG. The standard filter, however, is limited because the frequency of the baseline signal is variable and the baseline wander's spectrum overlaps with the ST segment's spectrum, and for the adaptive filter, it is difficult to select the reference signal. This study proposed a new, structured adaptive filter that is to remove noise without reference signal using neural networks. In order to confirm performance, this paper used ECG data of MIT-BIHs and obtained significant results through the tests.},
keywords={},
doi={},
ISSN={},
month={January},}

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TY - JOUR
TI - Adaptive Filtering for Baseline Wander Noise of ECG Using Neural Networks
T2 - IEICE TRANSACTIONS on Information
SP - 261
EP - 266
AU - Juwon LEE
AU - Weonrae JO
AU - Gunki LEE
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E87-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2004
AB - This study proposed the new method to minimize distortion of the ST segment and noise deletion of ECG baseline wander. In general, the standard filter and adaptive filter are used to remove the baseline wander of the ECG. The standard filter, however, is limited because the frequency of the baseline signal is variable and the baseline wander's spectrum overlaps with the ST segment's spectrum, and for the adaptive filter, it is difficult to select the reference signal. This study proposed a new, structured adaptive filter that is to remove noise without reference signal using neural networks. In order to confirm performance, this paper used ECG data of MIT-BIHs and obtained significant results through the tests.
ER -