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Journal ArticleDOI

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.

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Citations
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Journal ArticleDOI
TL;DR: A real-time system that uses wavelet transforms to overcome the limitations of other methods of detecting QRS and the onsets and offsets of P- and T-waves is described.
Abstract: The rapid and objective measurement of timing intervals of the electrocardiogram (ECG) by automated systems is superior to the subjective assessment of ECG morphology. The timing interval measurements are usually made from the onset to the termination of any component of the EGG, after accurate detection of the QRS complex. This article describes a real-time system that uses wavelet transforms to overcome the limitations of other methods of detecting QRS and the onsets and offsets of P- and T-waves. Wavelet transformation is briefly discussed, and detection methods and hardware and software aspects of the system are presented, as well as experimental results.

361 citations

Journal ArticleDOI
TL;DR: This work brings to the table the ECG signal and presents a thorough analysis of its psychological properties, differentiates for the first time between active and passive arousal, and advocates that there are higher chances of ECG reactivity to emotion when the induction method is active for the subject.
Abstract: Emotion modeling and recognition has drawn extensive attention from disciplines such as psychology, cognitive science, and, lately, engineering. Although a significant amount of research has been done on behavioral modalities, less explored characteristics include the physiological signals. This work brings to the table the ECG signal and presents a thorough analysis of its psychological properties. The fact that this signal has been established as a biometric characteristic calls for subject-dependent emotion recognizers that capture the instantaneous variability of the signal from its homeostatic baseline. A solution based on the empirical mode decomposition is proposed for the detection of dynamically evolving emotion patterns on ECG. Classification features are based on the instantaneous frequency (Hilbert-Huang transform) and the local oscillation within every mode. Two experimental setups are presented for the elicitation of active arousal and passive arousal/valence. The results support the expectations for subject specificity, as well as demonstrating the feasibility of determining valence out of the ECG morphology (up to 89 percent for 44 subjects). In addition, this work differentiates for the first time between active and passive arousal, and advocates that there are higher chances of ECG reactivity to emotion when the induction method is active for the subject.

357 citations

Book ChapterDOI
25 Oct 2010
TL;DR: Continuous stress monitoring may help users better under- stand their stress patterns and provide physicians with more reliable data for interventions and to exclude the effects of physical activity while developing a pervasive stress monitoring for everyday use.
Abstract: Continuous stress monitoring may help users better under- stand their stress patterns and provide physicians with more reliable data for interventions. Previously, studies on mental stress detection were lim- ited to a laboratory environment where participants generally rested in a sedentary position. However, it is impractical to exclude the effects of physical activity while developing a pervasive stress monitoring appli- cation for everyday use. The physiological responses caused by mental stress can be masked by variations due to physical activity.

354 citations


Cites methods from "A Real-Time QRS Detection Algorithm..."

  • ...For R-peak detection, we mainly adapted a derivative method [19] with modifications....

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Journal ArticleDOI
TL;DR: This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data and is able to classify the N, S, V, F and U arrhythmia classes with high accuracy.

335 citations


Cites methods from "A Real-Time QRS Detection Algorithm..."

  • ...B. QRS Complex-detection The Pan–Tompkins algorithm was used on the denoised ECG signal algorithm for detection of the QRS complex (Pan and Tompkins, 1985)....

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Proceedings ArticleDOI
22 Sep 2002
TL;DR: The open source QRS detectors have sensitivities and positive predictivities that are close to 99.8% on the MIT/BIH and AHA arrhythmia databases and the beat classifier has a sensitivity of 93.91% and a positive predictivity of 96.48%.
Abstract: Each year companies and researchers expend significant resources developing basic beat detection and classification software. In an effort to reduce this duplication of effort we are developing and making available open source ECG analysis software. Our open source QRS detectors have sensitivities and positive predictivities that are close to 99.8% on the MIT/BIH and AHA arrhythmia databases. Our beat classifier has a sensitivity of 93.91% and a positive predictivity of 96.48% on the MIT/BIH arrhythmia database and a sensitivity of 93.2% and a positive predictivity of 97.83% on the AHA arrhythmia database. Since we have posted our source code, over 350 users have downloaded our ECG analysis software. Downloads have been nearly equally divided between students, researchers, and commercial developers.

334 citations


Cites methods from "A Real-Time QRS Detection Algorithm..."

  • ...Our QRS detectors are based on the QRS detector originally developed by Pan and Tompkins [1] in assembly language for implementation on a Z80 microprocessor and later improved and ported to C by Hamilton and Tompkins [2]....

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  • ...described in [1] and [2] in its use of a rectified rather than a squared signal and an 80 ms averaging window rather than a 150 ms averaging window....

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References
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Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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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Journal ArticleDOI
P. A. Lynn1
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

Journal ArticleDOI
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