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Journal ArticleDOI

A Real-Time QRS Detection Algorithm

TLDR
A real-time algorithm that reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width of ECG signals and automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate.
Abstract
We have developed a real-time algorithm for detection of the QRS complexes of ECG signals. It reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width. A special digital bandpass filter reduces false detections caused by the various types of interference present in ECG signals. This filtering permits use of low thresholds, thereby increasing detection sensitivity. The algorithm automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate. For the standard 24 h MIT/BIH arrhythmia database, this algorithm correctly detects 99.3 percent of the QRS complexes.

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Proceedings ArticleDOI

Biophone: Physiology monitoring from peripheral smartphone motions

TL;DR: It is demonstrated that motion sensors available in off-the-shelf smartphones can capture physiological parameters of a person during stationary postures, even while being carried in a bag or a pocket, and methods to extract heart and breathing rates from accelerometer data are developed.
Posted Content

A Comparison of 1-D and 2-D Deep Convolutional Neural Networks in ECG Classification.

TL;DR: An ECG signal classification method based on the images is presented to classify ECG signals into normal and abnormal beats by using two-dimensional convolutional neural networks (2D-CNNs) to alleviate the overfitting problem in two- dimensional network.
Journal ArticleDOI

Development of a Wearable Mobile Electrocardiogram Monitoring System by Using Novel Dry Foam Electrodes

TL;DR: A wearable mobile electrocardiogram monitoring system that can monitor the user's ECG state continuously and anywhere in the globe if they are under the coverage of Global System for Mobile communications (GSM) cellular network is proposed.
Proceedings ArticleDOI

ECGNet: Deep Network for Arrhythmia Classification

TL;DR: Three robust deep neural network (DNN) architectures to perform feature extraction and classification of a given two second ECG signal are proposed and outperform the state-of-the art works on ECG classification on several metrics.
Journal ArticleDOI

An Automatic R and T Peak Detection Method Based on the Combination of Hierarchical Clustering and Discrete Wavelet Transform

TL;DR: This paper proposes a novel method for the R-peak and the T-peak detection using hierarchical clustering and Discrete Wavelet Transform (DWT) from the ECG signal.
References
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Journal ArticleDOI

Software QRS detection in ambulatory monitoring--a review.

TL;DR: This review asserts that most one-channel QRS detectors described in the literature can be considered as having the same basic structure and a discussion of some of the current detection schemes is presented.
Journal ArticleDOI

Optimal QRS detector.

TL;DR: The problem of detecting the QRS complex in the presence of noise was analysed and an optimised threshold criterion based on FP/FN was developed.
Journal ArticleDOI

Automated High-Speed Analysis of Holter Tapes with Microcomputers

TL;DR: An automated Holtes scanning system based on two microcomputers that detects QRS complexes and measures the QRS durations using computations of first and second derivatives, and can process Holter tapes at 60 times real time and produce printed summaries and 24 h trend plots.
Journal ArticleDOI

Online digital filters for biological signals: some fast designs for a small computer.

TL;DR: The possibilities for extending the class of lowpass recursive digital filters to include high pass, bandpass, and bandstop filters are described, and experience with a PDP 11 computer has shown that these filters may be programmed simply using machine code, and that online operation at sampling rates up to about 8 kHz is possible.
Journal ArticleDOI

A robust-digital QRS-detection algorithm for arrhythmia monitoring

TL;DR: In this paper a new robust single lead QRS-detection algorithm is presented, allowing real-time applications and results are presented.
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