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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Proceedings ArticleDOI
An efficient technique for automated diagnosis of cardiac rhythms using electrocardiogram
TL;DR: Pattern recognition and machine learning-based approach for computer-aided detection of five classes of ECG arrhythmia beats using Discrete Cosine Transform (DCT) coefficients is described, which has intensive applications in early diagnosis, mass screening of cardiac health and in cardiac theoretic devices such as pacemaker systems.
Ecg peak detection using wavelet transform
M. A. Khayer,M. A. Haque +1 more
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Proceedings ArticleDOI
Personalizing a Generic ECG Heartbeat Classification for Arrhythmia Detection: A Deep Learning Approach
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Journal ArticleDOI
VLSI Implementation of an Efficient Lossless EEG Compression Design for Wireless Body Area Network
TL;DR: An effective Very-Large-Scale Integration (VLSI) circuit design of lossless EEG compression circuit is proposed to increase both efficiency and effectivity of EEG signal transmission over WBAN.
Journal ArticleDOI
Reconfigurable Architecture for Multi-lead ECG Signal Compression with High-frequency Noise Reduction
TL;DR: This paper presents a reconfigurable signal processing unit which is implemented in ZedBoard- a development board for Xilinx Zynq −7000 SoC and can work in real-time and achieve a maximum 90% compression rate without any significant signal distortion.
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