Journal ArticleDOI
The impact of the MIT-BIH Arrhythmia Database
George B. Moody,Roger G. Mark +1 more
TLDR
The history of the database, its contents, what is learned about database design and construction, and some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database are reviewed.Abstract:
The MIT-BIH Arrhythmia Database was the first generally available set of standard test material for evaluation of arrhythmia detectors, and it has been used for that purpose as well as for basic research into cardiac dynamics at about 500 sites worldwide since 1980. It has lived a far longer life than any of its creators ever expected. Together with the American Heart Association Database, it played an interesting role in stimulating manufacturers of arrhythmia analyzers to compete on the basis of objectively measurable performance, and much of the current appreciation of the value of common databases, both for basic research and for medical device development and evaluation, can be attributed to this experience. In this article, we briefly review the history of the database, describe its contents, discuss what we have learned about database design and construction, and take a look at some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database.read more
Citations
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Journal ArticleDOI
ECG arrhythmia classification using modified visual geometry group network (mVGGNet)
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Cloud-based ECG monitoring using event-driven ECG acquisition and machine learning techniques
TL;DR: The experimental results show that grace of event-driven nature an overall 2.6 times compression and bandwidth utilization gain is attained by the suggested solution compared to the counter classical methods, indicating a significant reduction in the complexity and execution time of the post denoising, features extraction and classification processes.
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Explainable AI for Healthcare 5.0: Opportunities and Challenges
Deepti Saraswat,Pronaya Bhattacharya,Ashwin Verma,Vivek Kumar Prasad,Sudeep Tanwar,Gulshan Sharma,Pitshou Bokoro,Ravi Sharma +7 more
TL;DR: A proposed architecture that presents an EXAI ensemble on the computerized tomography (CT) image classification and segmentation process is unfolded that proves the efficacy of EXAI in health setups that envisions real-life model deployments in a wide range of clinical applications.
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Heart Monitor Using Flexible Capacitive ECG Electrodes
Yang Gao,Varun Soman,Jack P. Lombardi,Pravakar P. Rajbhandari,Tara P. Dhakal,Dale G. Wilson,Mark D. Poliks,Kanad Ghose,James N. Turner,Zhanpeng Jin +9 more
TL;DR: The challenge of high-gain low-noise amplification was met by the development of highly thinned OpAmps whose operation was shown to be equivalent to commercially available rigidly packaged Op amps, demonstrating that high-performance Si-electronics can be used to produce high-fidelity signals from weak biopotentials.
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An improved cardiac arrhythmia classification using an RR interval-based approach
TL;DR: An improved RR interval-based cardiac arrhythmia classification approach that is significantly better and more accurate than the other classifiers used in this method.
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