Methods of cardiac signal restoration and complex processing

Dushanov , Begmamat, Mamatov , Narzillo

Innovations in Science and Technologies · 2025-yil

Annotatsiya

Accurate restoration and complex processing of cardiac signals, i.e., electrocardiograms (ECG), are extremely crucial for reliable diagnosis and automatic detection of cardiovascular diseases. The present work gives a complete framework that includes signal restoration, denoising, feature extraction, and classification to enhance the precision of ECG analysis. Reconstruction of missing and corrupted cardiac segments is accomplished by Hermite polynomial interpolation with Chebyshev nodes and adaptive filtering by the Least Mean Squares (LMS) algorithm. Denoising is carried out by hybrid wavelet–CEEMDAN decomposition for attenuation of baseline drift, motion artifacts, and high-frequency noise without compromising morphological features. The proposed method then continues with the extraction of effective temporal, spectral, and nonlinear features—RR intervals, power spectral density, and sample entropy—prior to dimensionality reduction via Principal Component Analysis (PCA). The classification is finally carried out using deep convolutional neural networks (CNNs) with the MITBIH Arrhythmia Database as the training data. Experimental validation illustrates significant improvement in signal-to-noise ratio (SNR), percent root-mean-square difference (PRD), and F1- score compared to conventional techniques. The results validate that the proposed combination of advanced signal restoration and deep learning structures is a viable solution to precise ECG analysis and real-time cardiac monitoring.

Maqola ma’lumotlari
MualliflarDushanov , Begmamat, Mamatov , Narzillo
JurnalInnovations in Science and Technologies
NashriyotТошкент давлат иқтисодиёт университети
ISSN3030-3451
Nashr sanasi2025-10-27
Jild2
Son9
Betlar429-439
TilIngliz
Ilmiy sohaIqtisodiyot
Indeksga qo‘shilgan2026-08-26

Maqolaning asl sahifasi

Kalit so‘zlar

Electrocardiogram (ECG) signal restoration denoising, CEEMDAN, Hermite interpolation, adaptive filtering, wavelet transform, feature extraction, convolutional neural network (CNN), cardiac signal processing, arrhythmia detection, deep learning, biomedical signal analysis.

Ilmiy soha

Iqtisodiyot

Iqtibos keltirish

APADushanov , Begmamat, & Mamatov , Narzillo (2025). METHODS OF CARDIAC SIGNAL RESTORATION AND COMPLEX PROCESSING. Innovations in Science and Technologies, 2(9), 429-439. https://innoist.uz/index.php/ist/article/view/1299
GOST (OAK)Dushanov , Begmamat, Mamatov , Narzillo METHODS OF CARDIAC SIGNAL RESTORATION AND COMPLEX PROCESSING // Innovations in Science and Technologies. – 2025. – T. 2, № 9. – P. 429-439.
MLADushanov , Begmamat, and Mamatov , Narzillo. “METHODS OF CARDIAC SIGNAL RESTORATION AND COMPLEX PROCESSING.” Innovations in Science and Technologies, 2(9), 429-439, 2025. https://innoist.uz/index.php/ist/article/view/1299
ChicagoDushanov , Begmamat, and Mamatov , Narzillo. “METHODS OF CARDIAC SIGNAL RESTORATION AND COMPLEX PROCESSING.” Innovations in Science and Technologies, 2(9), 429-439 (2025). https://innoist.uz/index.php/ist/article/view/1299
HarvardDushanov , Begmamat, and Mamatov , Narzillo (2025) ‘METHODS OF CARDIAC SIGNAL RESTORATION AND COMPLEX PROCESSING’, Innovations in Science and Technologies, 2(9), 429-439. https://innoist.uz/index.php/ist/article/view/1299
BibTeX
@article{dushanovbegmamat2025,
  title = {METHODS OF CARDIAC SIGNAL RESTORATION AND COMPLEX PROCESSING},
  author = {Dushanov , Begmamat and Mamatov , Narzillo},
  journal = {Innovations in Science and Technologies},
  year = {2025},
  volume = {2},
  number = {9},
  pages = {429-439},
  url = {https://innoist.uz/index.php/ist/article/view/1299}
}

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