Temporal feature and heuristics-based Noise Detection over Classical Machine Learning for ECG Signal Quality Assessment

Indra Hermawan, M. A. Anwar Ma'sum, P. Riskyana Dewi Intan, Wisnu Jatmiko, Budi Wiweko, Alfred Boediman, Beno K. Pradekso

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study proposes a method for ECG signals quality assessment (SQA) by using temporal feature, and heuristic rule. The ECG signal will be classified as acceptable or unacceptable. Seven types of noise were able to be detected by the prosed method. The noises are: FL, TVN, BW, AB, MA, PLI and AWGN. The proposed method is aimed to have better performance for SQA than classical machine learning method. The experiment is conducted by using 1000 instances ECG signal. The experiment result shows that db8 has the best performance with 0.86, 0.85 and 85.6% on lead-1 signal and 0.69, 0.79, and 74% on lead-5 signal for specificity, sensitivity and accuracy respectively. Compared to the classical machine learning, the proposed heuristic method has same accuracy but has 48% and 31% better specificity for lead-1 and lead-5. It means that the proposed method has far better ability to detect noise.

Original languageEnglish
Title of host publication2019 International Workshop on Big Data and Information Security, IWBIS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781728153476
DOIs
Publication statusPublished - Oct 2019
Event2019 International Workshop on Big Data and Information Security, IWBIS 2019 - Bali, Indonesia
Duration: 11 Oct 2019 → …

Publication series

Name2019 International Workshop on Big Data and Information Security, IWBIS 2019

Conference

Conference2019 International Workshop on Big Data and Information Security, IWBIS 2019
CountryIndonesia
CityBali
Period11/10/19 → …

Keywords

  • classical machine learning
  • electrocardiogram
  • heuristic rule
  • signal quality
  • temporal features
  • wavelet

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  • Cite this

    Hermawan, I., Anwar Ma'sum, M. A., Riskyana Dewi Intan, P., Jatmiko, W., Wiweko, B., Boediman, A., & Pradekso, B. K. (2019). Temporal feature and heuristics-based Noise Detection over Classical Machine Learning for ECG Signal Quality Assessment. In 2019 International Workshop on Big Data and Information Security, IWBIS 2019 (pp. 1-8). [8935757] (2019 International Workshop on Big Data and Information Security, IWBIS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWBIS.2019.8935757