A Real-Time QRS Detection Algorithm
01 Mar 1985-IEEE Transactions on Biomedical Engineering (IEEE Trans Biomed Eng)-Vol. 32, Iss: 3, pp 230-236
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.
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.
Citations
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TL;DR: ICA can be considered as notably the best approach to reduce ventricular activity from unipolar atrial electrograms in organized atrial arrhythmias.
Abstract: Atrial fibrillation is a very common cardiovascular disease in clinical practice. One relevant issue to understand its pathophysiological mechanisms is the analysis and interpretation of atrial electrograms (AEG). To study these signals properly, ventricular activity has to be removed from the AEG. In this work, a new application of independent component analysis (ICA) to the AEG is presented, where ventricular activity is removed from atrial epicardial recordings making use of only one reference lead. Therefore the technique is suitable when multi-lead recordings are unavailable as in atrial implantable cardioverter defibrilators. In addition to the proposed new methodology this work also presents the first comparative study, making use of unipolar epicardial AEGs, among the ICA-based technique, template matching and subtraction (TMS), and adaptive ventricular cancellation (AVC) on a database of 20 patients. A performance comparative analysis was carried out by evaluating epicardial atrial waveform similarity (S) and ventricular depolarization reduction (VDR) as a function of atrial rhythm regularity on a beat-by-beat basis. Results indicate that, when the epicardial atrial rhythm is quite organized, ICA is able to preserve the atrial waveform very precisely and better than the other methods (median S = 99.64% ± 0.31% in contrast to 95.18% ± 2.71% for TMS and 94.76% ± 4.12% for AVC). Moreover, ventricular reduction is the best for ICA (median VDR = 6.32 ± 4.41 dB in contrast to 4.98 ± 4.48 dB for TMS and 4.12 ± 2.72 dB for AVC). On the other hand, when the atrial activity is disorganized, TMS notably improves performance (S = 97.72% ± 1.87%), but ICA still is the best in waveform preservation (S = 98.22% ± 1.53%) whereas AVC remains similar (S = 93.74% ± 4.38%). In conclusion, ICA can be considered as notably the best approach to reduce ventricular activity from unipolar atrial electrograms in organized atrial arrhythmias. On the other hand, both TMS and ICA give quite similar results when the atrial arrhythmia is disorganized.
53 citations
TL;DR: This work extracted nonlinear features from the HRV signals using the following techniques: recurrence plots (RP), Poincare plots, and detrended fluctuation analysis (DFA), and observed that the multilayer perceptron (MLP) method resulted in the highest classification accuracy using the proposed technique.
Abstract: Coronary artery disease (CAD) is a leading cause of death worldwide. Heart rate variability (HRV) has been proven to be a non-invasive marker of the autonomic modulation of the heart. Nonlinear analyses of HRV signals have shown that the HRV is reduced significantly in patients with CAD. Therefore, in this work, we extracted nonlinear features from the HRV signals using the following techniques: recurrence plots (RP), Poincare plots, and detrended fluctuation analysis (DFA). We also extracted three types of entropy, namely, Shannon entropy (ShanEn), approximation entropy (ApEn), and sample entropy (SampEn). These features were subjected to principal component analysis (PCA). The significant principal components were evaluated using eight classification techniques, and the performances of these techniques were evaluated to determine which presented the highest accuracy in classifying normal and CAD classes. We observed that the multilayer perceptron (MLP) method resulted in the highest classification accuracy (89.5%) using our proposed technique.
53 citations
Additional excerpts
...The R peaks of ECG signal were detected using Tompkins's algorithm.(19,20) Novel Classi ̄cation of Coronary Artery Disease Using Heart Rate Variability Analysis...
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08 Mar 2009
TL;DR: Various QRS detection methods used to derive heart rate variability (HRV) are described and various time and frequency domain HRV parameters are reviewed.
Abstract: Electrocardiogram (ECG) is one of the most important physiological parameter that gives correct assessment of heart function. QRS complex is a prominent waveform in an ECG that provides the basis for analyzing heart rate variability (HRV). HRV refers to the beat-to-beat alterations in heart rate. Commercial devices these days provide preset computerized measurement of HRV, thus providing the cardiologist a simple tool for both research and clinical learning. To obtain meaningful data from the ECG, a noise free inter-beat interval (IBI) time series is required to be extracted. This is realized using standard peak detection algorithms packed with data acquisition hardware and software. The aim of this paper is to describe various QRS detection methods used to derive HRV. It also reviews various time and frequency domain HRV parameters. The significance and meaning of these different measures of HRV are a potential area of research.
53 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...The method is however prone to noise [10]....
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Patent•
22 Oct 2012
TL;DR: In this article, the authors describe sensors mounted on a textile include at least one of electrically conductive textile electrodes; single or multiple optically coupled infrared and red emitter and photodiode or photo transistor; and thin film or Resistive Temperature Detector (RTD).
Abstract: Sensors mounted on a textile include at least one of electrically conductive textile electrodes; single or multiple optically coupled infrared and red emitter and photodiode or photo transistor; and thin film or Resistive Temperature Detector (RTD). Textile electrodes, electrical connections, and electrical functionalization use at least one of nanoparticles, nanostructures, and mesostructures. Conductive thread, for electrical connections, may include a fiber core made from conductive materials such as but not limited to metals, alloys, and graphine structures, and a sheath of insulating materials such as but not limited to nylon, polyester, and cotton.
53 citations
TL;DR: Omgarments provide high signal quality for adequate rhythm analysis, representing a promising novel technology for long-term non-invasive ECG monitoring.
53 citations
References
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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.
Abstract: The QRS detection algorithm is an essential part of any computer-based system for the analysis of ambulatory ECG recordings. This review asserts that most one-channel QRS detectors described in the literature can be considered as having the same basic structure. A discussion of some of the current detection schemes is presented with regard to this structure. Some additional features of QRS detectors are mentioned. The evaluation of performance and the problem of multichannel detection, which is now gaining importance, are also briefly treated.
254 citations
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.
Abstract: The problem of detecting the QRS complex in the presence of noise was analysed. Most QRS detectors contain a filter to improve the signal-to-noise ratio and compare the signal with a threshold. In an earlier paper we identified an optimal filter. Various techniques to generate threshold and detector designs were studied. Automatic gain-control circuits with a fixed threshold have a very slow response to different rhythms. Automatic threshold circuits based on simple peak-detection schemes have a fast response, but are very sensitive to sudden variations in QRS amplitudes and noise transients. None of the methods described to date present any optimisation criteria for detecting the signal (QRS complex) in the presence of noise. The probabilities of FPs (false positives) and FNs (false negatives) were investigated and an optimised threshold criterion based on FP/FN was developed. Presently, data are being collected to compare various techniques from their ROC (receiver operating characteristics).
151 citations
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.
Abstract: We have developed an automated Holtes scanning system based on two microcomputers. One is a preprocessor that detects QRS complexes and measures the QRS durations using computations of first and second derivatives. Thismicrocomputer interfaces to a secondmicro-computer that does arrhythmia analysis, logging, and reporting using R-R intervals and QRS durations. This system can process Holter tapes at 60 times real time and produce printed summaries and 24 h trend plots of several variables including heart rate and PVC count.
127 citations
"A Real-Time QRS Detection Algorithm..." refers methods in this paper
...The slope of the R wave is a popular signal feature used to locate the QRS complex in many QRS detectors [5]....
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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.
Abstract: After reviewing the design of a class of lowpass recursive digital filters having integer multiplier and linear phase characteristics, the possibilities for extending the class to include high pass, bandpass, and bandstop (‘notch’) filters are described. 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. The practical application of such filters is illustrated by using a notch desgin to remove mains-frequency interference from an e.c.g. waveform.
104 citations
TL;DR: In this paper a new robust single lead QRS-detection algorithm is presented, allowing real-time applications and results are presented.
101 citations