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A Real-Time QRS Detection Algorithm

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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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Journal ArticleDOI

MEDIC: Medical embedded device for individualized care

TL;DR: By using commercially available hardware components and software architecture presented in this paper, the MEDIC system can be rapidly configured, providing medical researchers with broadband sensor data from remote patients and platform access to best adapt operation for diagnostic operation objectives.
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Automated diagnosis of coronary artery disease (CAD) patients using optimized SVM

TL;DR: This study has shown that methods which are based on the feature extraction of the biomedical signals are an appropriate approach to predict the health situation of the patients.
Journal ArticleDOI

Adaptive singular value cancelation of ventricular activity in single-lead atrial fibrillation electrocardiograms

TL;DR: The study has proven that optimal VA cancelation is achieved when a number between 20 and 30 complexes is selected following a correlation-based strategy and provides a more accurate beat-to-beat ventricular QRST representation than traditional techniques.
Journal ArticleDOI

Detection of ECG characteristic points using Multiresolution Wavelet Analysis based Selective Coefficient Method

TL;DR: A multiresolution wavelet transform based system for detection and evaluation of QRS complex, P and T waves and validated using original 12 lead ECG recording collected from the physionet PTB diagnostic database.
Journal ArticleDOI

Towards a generalized scheme for QRS detection in ECG waveforms

F. Gritzali
- 01 Sep 1988 - 
TL;DR: Two transformations are proposed in this paper that can be used for QRS detection in one-channel as well as in multi-channel ECGs, with very good performance.
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.
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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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