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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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Proceedings ArticleDOI
11 Jun 2017
TL;DR: The development of prototype that enables monitoring of heart rate and inter beat interval for several subjects is described and one of the possible realizations of group monitoring of biomedical data is shown.
Abstract: Paper describes the development of prototype that enables monitoring of heart rate and inter beat interval for several subjects. The prototype was realized using ESP8266 hardware modules, WebSocket library, nodejs and JavaScript. System architecture is described where nodejs server acts as the signal processing and GUI code provider for clients. Signal processing algorithm was implemented in JavaScript. Application GUI is presented which can be used on mobile devices. Several important parts of the code are described which illustrate the communication between ESP8266 modules, server and clients. Developed prototype shows one of the possible realizations of group monitoring of biomedical data.

44 citations


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

  • ...Detecting heart rate is one of the main tasks that has been addressed historically [1] as well as recently [2–5]....

    [...]

Journal ArticleDOI
TL;DR: In this paper, a novel fractional wavelet transform (FrWT) is used as a preprocessing tool to detect arrhythmia in ECG signal wave components (PQRS-T) for a time duration.
Abstract: Any significant alteration in the Electro-Cardio-Gram (ECG) signal wave components (P-QRS-T) for a time duration is detected as arrhythmia. In this paper, a novel fractional wavelet transform (FrWT) is used as a preprocessing tool. FrWT describes the given signal in time–frequency fractional domain using fractional Fourier transform and its denoising using wavelet transform. Because of this novel and intriguing property, it is broadly utilized as a noise removal tool in the fractional domain along with multiresolution analysis. Next, features are extracted using Yule–Walker autoregressive modeling. Dimensionality of the extracted features is to be reduced for proper detection of different types of arrhythmias. Principal component analysis has been applied for arrhythmia detection using variance estimation. The proposed method is evaluated on the basis of various performance parameters such as output SNR, mean squared error (MSE) and detection accuracy ( $$ {\text{DE}}_{\text{Acc}} $$ ). An output SNR of 33.41 dB, MSE of 0.1689% and Acc of 99.94% for real-time ECG database and output SNR of 25.25 dB, MSE of 0.1656%, $$ {\text{DE}}_{\text{Acc}} $$ of 99.89% for MIT-BIH Arrhythmia database are obtained.

44 citations

Journal ArticleDOI
TL;DR: Wavelet transformation can be a useful technique to detect the primary potentials and quantify the degree of fractionation of fibrillation electrograms, which could enable real-time mapping of complex cases of human AF and classification of the underlying electropathological substrate.
Abstract: This study introduces the use of wavelet decomposition of unipolar fibrillation electrograms for the automatic detection of local activation times during complex atrial fibrillation (AF). The purpose of this study was to evaluate this technique in patients with structural heart disease and longstanding persistent AF. In 46 patients undergoing cardiac surgery, unipolar fibrillation electrograms were recorded from the right atrium, using a mapping array of 244 electrodes. In 25 patients with normal sinus rhythm, AF was induced by rapid pacing, whereas 21 patients were in persistent AF. In patients with longstanding AF, the atrial electrograms showed a high degree of fractionation. In each patient, 12 s of AF were analyzed by wavelet transformation (15 scales). The finest scales (1-7) were used to reconstruct a “local” fibrillation electrogram, whereas with the coarse scales (9-15), a far-field signal was generated. With these local and far-field electrograms, the “primary” fibrillation potentials, due to wave propagation underneath the electrode, could be distinguished from double potentials and multiple components generated by remote wavefronts. Wavelet transformation resulted in AF histograms with a closely Gaussian distribution and the automatically generated activation maps showed a good resemblance with fibrillation maps obtained by laborious manual editing. A special chaining algorithm was developed to detect multiple components in fractionated electrograms. The degree of fractionation showed a positive correlation with the complexity of fibrillation, thus providing an objective quantification of the degree of electrical dissociation of the atria. Wavelet transformation can be a useful technique to detect the primary potentials and quantify the degree of fractionation of fibrillation electrograms. This could enable real-time mapping of complex cases of human AF and classification of the underlying electropathological substrate.

44 citations

Proceedings ArticleDOI
28 May 2014
TL;DR: Embedded services that are part of a ubiquitous healthcare system that allows automated and intelligent monitoring, that uses IP connectivity and the Internet for end-to-end communication, from each 6LoWPAN sensor nodes to the web user interface on the Internet.
Abstract: The continuous advancement in computer and communication technologies has made personalized healthcare monitoring a rapidly growing area of interest. New features and services are envisaged, raising users' expectations in healthcare services. The emergence of Internet of Things brings people closer to connect the physical world to the Internet. In this paper, we present embedded services that are part of a ubiquitous healthcare system that allows automated and intelligent monitoring. The system uses IP connectivity and the Internet for end-to-end communication, from each 6LoWPAN sensor nodes to the web user interface on the Internet. The proposed algorithm in the Gateway performs multithreaded processing on the gathered medical signals for conversion to real data, feature extraction and wireless display. The user interface at the server allows users to access and view the medical data from mobile and portable devices. The ubiquitous system is exploring possibilities in connecting Internet with things and people for health services.

44 citations


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

  • ...A real-time QRS detection algorithm that is based on analysis of slope, amplitude and width of QRS complexes algorithm is adopted [11]....

    [...]

Proceedings ArticleDOI
01 Oct 2016
TL;DR: This paper focuses on the use of electrocardiogram (ECG) signals to implement distributed biometrics authentication within an IoT system model and shows that ECGBiometrics are highly reliable, more secure, and easier to implement than other biometric methods.
Abstract: The Internet of Things (IoT) is a design implementation of embedded system design that connects a variety of devices, sensors, and physical objects to a larger connected network (e.g. the Internet) which requires human-to-human or human-to-computer interaction. While the IoT is expected to expand the user's connectivity and everyday convenience, there are serious security considerations that come into account when using the IoT for distributed authentication. Furthermore the incorporation of biometrics to IoT design brings about concerns of cost and implementing a ‘user-friendly’ design. In this paper, we focus on the use of electrocardiogram (ECG) signals to implement distributed biometrics authentication within an IoT system model. Our observations show that ECG biometrics are highly reliable, more secure, and easier to implement than other biometrics.

44 citations


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

  • ...In this paper, we use the R peak detection algorithm proposed by Pan-Tompkins [29]....

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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]....

    [...]

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