Article Fingerprint
ReserarchID
OW6BN
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
This paper attempted to assess the attitudes of students in
Advances in technology have created the potential for a new
Inclusion has become a priority on the global educational agenda,
Automated ECG diagnosis (AED) & classification is essential to the timely diagnosis of potentially lethal heart conditions in clinical settings. In noisy environment, ECG feature extraction problem with considerable accuracy still remains open for research. Although, Wavelet Transform (WT) has been proved to be more prominent approach than any other conventional detection algorithms, but much abstruse to implement in commercial software. To reduce this implementation complexity, in this work, a combination of DWT and FFT-IFFT pair is proposed with Adaptive thresholding technique. MATLAB analysis supports this preprocessing and automatic detection idea in terms of accuracy. A software implementation of this AED system is presented here in .net framework which can be interfaced with any commercial ECG machine by changing some parameters.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
