Wavelet-Based Signal Quality Assessment: Noise Detection by Temporal Feature and Heuristics-based

Hermawan, Indra; Sevani, Nina; Ma’sum, M. Anwar; Alfiany, Noverina; Jatmiko, Wisnu

doi:10.1109/cyberneticscom.2019.8875655

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Kuzilek et al proposed an ECG signal quality assessment by using support vector machine (SVM) classifier [5]. Hermawan et al proposed ECG signal quality assessment using temporal feature and heuristic-based (rule-based) method [6]. Hermawan et al also measure the performance of the method compared with fully supervised classical machine learning method [7].…”

Section: Introductionmentioning

confidence: 99%

Improving Convolutional Neural Network with Recurrent Model and Generative Adversarial Networks for Imbalance Classification of Wearable ECG Signal Quality Assessment

Ma’sum

2022

J-Cosine

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Signal quality assessment is important procedure to assess if a signal can be preprocessed into next step or not. In this study, we proposed an improving of convolutional neural network with recurrent model and generative adversarial network. The experiment shows that enhancing convolutional neural network by using recurrent model or data augmentation via GAN for wearable ECG signal quality assessment is feasible to try. Adding recurrent model to CNN increase its performance by approximately 3% margin in un-augmented dataset. Generating fake samples from “unacceptable” class can enhance CNN performance up to 2% margin. Combination of recurrent model and GAN still not yet matched found. However, It doesn’t mean that the combination is impossible to do.

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Section: Introductionmentioning

confidence: 99%

Improving Convolutional Neural Network with Recurrent Model and Generative Adversarial Networks for Imbalance Classification of Wearable ECG Signal Quality Assessment

Ma’sum

2022

J-Cosine

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“…In [16, 17], LF and HF information of local waves of ECG signals and noises are extracted using various decomposition techniques followed by different temporal features for the detection and classification of ECG noises. In [18], a Daubechies wavelet‐based method is proposed for assessing the ECG signal with unacceptable quality using heuristic rules and temporal features.…”

Section: Introductionmentioning

confidence: 99%

Detection and classification of ECG noises using decomposition on mixed codebook for quality analysis

Kumar

Sharma

2020

Healthcare Technology Letters

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Automatic detection of poor quality signals as a pre-processing scheme in the analysis of sEMG in swallowing

Cuadros-Acosta

Duque

2022

Biomedical Signal Processing and Control

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Wavelet-Based Signal Quality Assessment: Noise Detection by Temporal Feature and Heuristics-based

Cited by 3 publications

References 9 publications

Improving Convolutional Neural Network with Recurrent Model and Generative Adversarial Networks for Imbalance Classification of Wearable ECG Signal Quality Assessment

Improving Convolutional Neural Network with Recurrent Model and Generative Adversarial Networks for Imbalance Classification of Wearable ECG Signal Quality Assessment

Detection and classification of ECG noises using decomposition on mixed codebook for quality analysis

Automatic detection of poor quality signals as a pre-processing scheme in the analysis of sEMG in swallowing

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