Journal ArticleDOI
Quality Aware Compression of Multilead Electrocardiogram Signal using 2-mode Tucker Decomposition and Steganography
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TLDR
A quality controlled compression of multilead electrocardiogram (MECG) is proposed, based on tensor analysis, and implemented upon 3D beat tensor of MECG, and has provided superior result as compared to recently published works on M ECG data compression.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2021-02-01. It has received 9 citations till now. The article focuses on the topics: Tucker decomposition & Data compression.read more
Citations
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Journal ArticleDOI
An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour
V.V.S. Sasank,S. Venkateswarlu +1 more
TL;DR: The Modified Sunflower Optimization (MSFO) algorithm is hybrid along with LBM which optimally selects the parameters that maximize the performance of tumour growth model.
Journal ArticleDOI
Deep neural network based missing data prediction of electrocardiogram signal using multiagent reinforcement learning
TL;DR: Bidirectional long short-term memory recurrent neural network based prediction of missing segment of ECG signal is accomplished, governed by reinforcement learning (RL) using multiagent, applicable to any single channel ECG signals.
Journal ArticleDOI
An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour
TL;DR: In this paper , the Modified Sunflower Optimization (MSFO) algorithm is hybrid along with Lattice Boltzmann Method (LBM) which optimally selects the parameters that maximize the performance of tumour growth model.
Journal ArticleDOI
Monte Carlo Filter-Based Motion Artifact Removal From Electrocardiogram Signal for Real-Time Telecardiology System
TL;DR: In this article, the Monte Carlo filter (MCF)-based MA removal from single-channel ECG signal is proposed, assisting in real-time telecardiology systems, and the proposed algorithm was tested on the IEEE Signal Processing Cup Challenge 2015 ECG database and MIT-BIH arrythmia records, with an improvement of signal-to-noise ratio between 10 and 15 dB.
Journal ArticleDOI
Quality Guaranteed ECG Signal Compression Using Tunable-Q Wavelet Transform and Möbius Transform-Based AFD
TL;DR: In this paper, a combination of tunable-Q wavelet transform (TQWT) and adaptive Fourier decomposition (AFD) was used for ECG signal compression.
References
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Journal ArticleDOI
Principal Component Analysis as a Tool for Analyzing Beat-to-Beat Changes in ECG Features: Application to ECG-Derived Respiration
TL;DR: An algorithm for analyzing changes in ECG morphology based on principal component analysis (PCA) is presented and applied to the derivation of surrogate respiratory signals from single-lead ECGs.
Journal ArticleDOI
Wavelet-Based ECG Steganography for Protecting Patient Confidential Information in Point-of-Care Systems
Ayman Ibaida,Ibrahim Khalil +1 more
TL;DR: A wavelet-based steganography technique has been introduced which combines encryption and scrambling technique to protect patient confidential data and it is found that the proposed technique provides high-security protection for patients data with low distortion and ECG data remain diagnosable after watermarking.
Posted Content
Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm
TL;DR: Zhang et al. as mentioned in this paper proposed a tensor robust principal component analysis (TRPCA) model based on the tensor-tensor product (or t-product) to recover the low-rank and sparse components from their sum.
Journal ArticleDOI
ECG coding by wavelet-based linear prediction
A. G. Ramakrishnan,Saikat Saha +1 more
TL;DR: The significant feature of the proposed technique is that, while the error is nearly uniform throughout the cycle, the diagnostically crucial QRS region is kept free of maximal reconstruction error.
Journal ArticleDOI
Multichannel ECG Data Compression Based on Multiscale Principal Component Analysis
TL;DR: Multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression and the lowest mean opinion score error value of 5.56% is found.