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Proceedings ArticleDOI

A new QRS detection algorithm based on the Hilbert transform

TLDR
A robust new algorithm for QRS defection using the properties of the Hilbert transform is proposed, which allows R waves to be differentiated from large, peaked T and P waves with a high degree of accuracy and minimizes the problems associated with baseline drift, motion artifacts and muscular noise.
Abstract
A robust new algorithm for QRS defection using the properties of the Hilbert transform is proposed. The method allows R waves to be differentiated from large, peaked T and P waves with a high degree of accuracy and minimizes the problems associated with baseline drift, motion artifacts and muscular noise. The performance of the algorithm was tested using the records of the MIT-BIH Arrhythmia Database. Beat by beat comparison was performed according to the recommendation of the American National Standard for ambulatory ECG analyzers (ANSI/AAMI EC38-1998). A QRS detection rate of 99.64%, a sensitivity of 99.81% and a positive prediction of 99.83% was achieved against the MIT-BIH Arrhythmia database. The noise tolerance of the new proposed QRS detector was also tested using standard records from the MIT-BIH Noise Stress Test Database. The sensitivity of the detector remains about 94% even for signal-to-noise ratios (SNR) as low as 6 dB.

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Citations
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Extraction and Detection of Fetal Electrocardiograms from Abdominal Recordings

TL;DR: To improve NIFECG extraction, the dynamic model of a Kalman filter approach was extended, providing a more adequate representation of the mixture of FECG, MECG, and noise, and these quality metrics were applied in improving FQRS detection and fetal heart rate estimation based on an innovative evolutionary algorithm and Kalman filtering signal fusion, respectively.
Journal ArticleDOI

Periodicity-based nonlocal-means denoising method for electrocardiography in low SNR non-white noisy conditions

TL;DR: The proposed periodic NLM filtering for ECG was applied to ECG signals and achieved results comparable to those of other state-of-the-art filters, especially for low SNR input.
Journal ArticleDOI

A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

TL;DR: Through connected telehealth care devices, the telesurveillance system, and the automatic ECG interpretation system, this mechanism was intentionally designed for continuous decision-making support and is reliable enough to reduce the need for face-to-face diagnosis.
Journal ArticleDOI

An Adaptive Median Filter Based on Sampling Rate for R-Peak Detection and Major-Arrhythmia Analysis.

TL;DR: An R-point detection method using an adaptive median filter based on the sampling rate and analyze major arrhythmias using the signal characteristics is proposed and experimental results indicated the effectiveness of the proposed R- point detection method and arrhythmia analysis technique.
Proceedings ArticleDOI

Data fusion for QRS complex detection in multi-lead electrocardiogram recordings

TL;DR: In this article, the authors presented a multi-lead detection approach, analyzing how many leads are necessary in order to observe an improvement in the detection performance, and proposed various data fusion techniques to combine the detections made by an algorithm.
References
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Book

Discrete-Time Signal Processing

TL;DR: In this paper, the authors provide a thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete time Fourier analysis.
Journal ArticleDOI

A Real-Time QRS Detection Algorithm

TL;DR: 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.
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The Fourier Transform and Its Applications

TL;DR: In this paper, the authors provide a broad overview of Fourier Transform and its relation with the FFT and the Hartley Transform, as well as the Laplace Transform and the Laplacian Transform.
Journal ArticleDOI

Detection of ECG characteristic points using wavelet transforms

TL;DR: An algorithm based on wavelet transforms (WT's) has been developed for detecting ECG characteristic points and the relation between the characteristic points of ECG signal and those of modulus maximum pairs of its WT's is illustrated.
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