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: The findings validate the use of Immersive Virtual Environments to elicit and automatically recognize different emotional states from neural and cardiac dynamics; this development could have novel applications in fields as diverse as Architecture, Health, Education and Videogames.
Abstract: Affective Computing has emerged as an important field of study that aims to develop systems that can automatically recognize emotions. Up to the present, elicitation has been carried out with non-immersive stimuli. This study, on the other hand, aims to develop an emotion recognition system for affective states evoked through Immersive Virtual Environments. Four alternative virtual rooms were designed to elicit four possible arousal-valence combinations, as described in each quadrant of the Circumplex Model of Affects. An experiment involving the recording of the electroencephalography (EEG) and electrocardiography (ECG) of sixty participants was carried out. A set of features was extracted from these signals using various state-of-the-art metrics that quantify brain and cardiovascular linear and nonlinear dynamics, which were input into a Support Vector Machine classifier to predict the subject’s arousal and valence perception. The model’s accuracy was 75.00% along the arousal dimension and 71.21% along the valence dimension. Our findings validate the use of Immersive Virtual Environments to elicit and automatically recognize different emotional states from neural and cardiac dynamics; this development could have novel applications in fields as diverse as Architecture, Health, Education and Videogames.
237 citations
TL;DR: This paper has studied the application on the fuzzy-hybrid neural network for electrocardiogram (ECG) beat classification and used autoregressive model coefficients, higher-order cumulant and wavelet transform variances as features.
235 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...The pattern recognition of the type of ECG waveform, different solutions presented in the literature, such MLP approach (Hu and Tompkins, 1985), the self-organizing map (Hu et al., 1997) are given....
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...The pattern recognition of the type of ECG waveform, different solutions presented in the literature, such MLP approach (Hu and Tompkins, 1985), the self-organizing map (Hu et al....
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TL;DR: The heart rate variability is used as the base signal from which certain parameters are extracted and presented to the ANN for classification, and the same data is also used for fuzzy equivalence classifier.
233 citations
Cites background from "A Real-Time QRS Detection Algorithm..."
...from which certain parameters are extracted for classi�cation [2, 3 ]....
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TL;DR: The proposed method is advantageous because it uses only the RR-interval signal for arrhythmia beat and episode classification and the results compare well with more complex methods.
231 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...If: the beat does not belong to an atrial fibrillation episode (AFIB), an atrial flutter episode (AFL) or a 28 heart block episode (BII) then: it is annotated using the MIT-BIH arrhythmia database beat annotation....
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TL;DR: An Empirical Mode Decomposition (EMD) based ECG signal enhancement and QRS detection algorithm is proposed and a single fold processing of each signal is required unlike other conventional techniques.
229 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...In many nonsyntactic methods like [9,10]; for QRS detection, P and T waves and noises are suppressed by bandpass filtering and some nonlinear transformation is performed for QRS complex enhancement....
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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