ECG modeling has wide application in signal representation, compression and synthetic ECG generation. CardioSim generates synthetic ECG waveform in real-time using PC-based system. It provides dual facility of interface-based visualization with hardware-based waveform generation. It has two stages viz., development of reference model parameter database using Fourier model and generation of synthetic ECG waveform based on user defined parameters using normal and abnormal records (H, APC, PVC, LBBB, RBBB, P) from mitdb under PhysioNet. It generates ten various ECG waveforms including one healthy and nine diseased rhythms from a single dynamic model with flexible user defined parameters. It gives higher reconstruction performance in terms of SNR and MSE. The mean SNR for different beat morphology is 89.2(H), 88.37(V), 86.32(A), 85.35(L), 97.22(P) and 83.3(R) and mean MSE is 2.45 × 10(H), 3.14 × 10(V), 8.98 × 10(A), 5.82 × 10(L), 0.43 × 10(P) and 0.25 × 10(R). It improves the performance parameters over published research work on ECG modeling and simulation. It can be used as a self-learning tool for entry level medical students.
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http://dx.doi.org/10.1080/10255842.2022.2127318 | DOI Listing |
Generative Adversarial Networks (GANs) have emerged as a powerful tool in artificial intelligence, particularly for unsupervised learning. This systematic review analyzes GAN applications in healthcare, focusing on image and signal-based studies across various clinical domains. Following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we reviewed 72 relevant journal articles.
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Department of Animal Science, University of São Paulo, Piracicaba, SP, Brazil, 13418-900. Electronic address:
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The Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, 1800 Lihu Road, Wuxi 214122, PR China. Electronic address:
Intrinsic environmental instability of hydrogels has limited their practical applications as durable flexible sensors in human life. In this study, a bio-based eutectogel (BEG) with environmental tolerance was designed via deep eutectic solvent (DES), thioctic acid (TA) and lignin. Benefit from self-ring-opening polymerization of TA monomer in the ethanol and the lignin acting as free radicals, the BEG was fabricated through efficient cast-drying method.
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Comput Biol Med
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Institute of Digital Technologies for Personalized Healthcare MeDiTech, Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Via la Santa 1, Lugano, 6900, Switzerland.
The scientific community has recently shown increasing interest in generating synthetic ECG data. In particular, synthetic ECG signals can be beneficial for understanding cardiac electrical activity, developing large and heterogeneous unbiased datasets, and anonymizing data to favour knowledge sharing and open science. In the present scoping review, various methodologies to generate synthetic ECG data have been thoroughly analysed, highlighting their limitations and possibilities.
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