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Journal ArticleDOI

Fast QRS Detection and ECG Compression Based on Signal Structural Analysis

Antoni Burguera
- 01 Jan 2019 - 
- Vol. 23, Iss: 1, pp 123-131
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TLDR
This study offers a parameterless and computationally efficient alternative for QRS complex detection and lossy ECG compression and some of the presented techniques are general enough to be used by other ECG analysis tools.
Abstract
Objective : This paper presents a fast approach to detect QRS complexes based on a simple analysis of the temporal ECG structure. Methods : The ECG is processed through several steps involving noise removal, feature detection, and feature analysis. The obtained feature set, which holds most of the ECG information while requiring low data storage, constitutes a lossy compressed version of the ECG. Results : The experiments, performed using 12 different ECG databases, emphasize the advantages of our proposal. For example, 130-min ECG recordings are processed in average in 0.77 s. Also, sensitivities and positive predictions surpass 99.9% in some databases, and a global data saving of 90.35% is achieved. Conclusion and significance : When compared to other approaches, this study offers a parameterless and computationally efficient alternative for QRS complex detection and lossy ECG compression. Moreover, some of the presented techniques are general enough to be used by other ECG analysis tools. Finally, the documented source code corresponding to this study is publicly available.

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Citations
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Journal ArticleDOI

An Efficient and Robust Digital Fractional Order Differentiator Based ECG Pre-Processor Design for QRS Detection

TL;DR: This paper presents an efficient infinite impulse response type digital fractional order differentiator (DFOD) based electrocardiogram (ECG) pre-processor to detect QRS complexes for the first time when the evolutionary algorithm based IIR-type DFOD is employed and establishing its performance superiority.
Journal ArticleDOI

Automatic Detection of QRS Complexes Using Dual Channels Based on U-Net and Bidirectional Long Short-Term Memory

TL;DR: Experimental results prove that the proposed method may be useful for automatic detection of QRS complex task, and can be extended to other medical signal research fields.
Journal ArticleDOI

An optimally designed digital differentiator based preprocessor for R-peak detection in electrocardiogram signal

TL;DR: The proposed IODD based QRS detection approach is validated on the first channel records of MIT/BIH Arrhythmia database (MBAD), QT database (QTDB), MIT/biH noise stress test database (NSTDB), atrial fibrillation termination challenge database (AFTDB, and MIT/ BIH ST change database (STDB) and ensures the accuracy of the proposed R-peak detection technique for a wide variety of QRS morphologies.
Journal ArticleDOI

Dynamic thresholding based efficient QRS complex detection with low computational overhead

TL;DR: A window-based FIR filter is used to eliminate the high-frequency noise and Kurtosis coefficient computation is used for discarding prominent T-wave and this technique located the QRS-complex accurately in the raw ECG signal.
Journal ArticleDOI

Optimal SSA‐based wideband digital differentiator design for cardiac QRS complex detection application

TL;DR: The simulation results and the root mean square magnitude error metric justify the superiority of the proposed SSA‐based DD design as compared with all other differentiators employed in the QRS complex detection application, and the reported first‐order DDs based on the numerical methods and the other evolutionary algorithms.
References
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Journal ArticleDOI

PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

TL;DR: The newly inaugurated Research Resource for Complex Physiologic Signals (RRSPS) as mentioned in this paper was created under the auspices of the National Center for Research Resources (NCR Resources).
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.
Journal ArticleDOI

The impact of the MIT-BIH Arrhythmia Database

TL;DR: 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.
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.
Journal ArticleDOI

A wavelet-based ECG delineator: evaluation on standard databases

TL;DR: A robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT), outperforming the results of other well known algorithms, especially in determining the end of T wave.
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