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: A protocol for monitoring the cardiac activity measuring the skin surface vibrations of the main neck vessels, caused by vascular wall motion in carotid artery is established, based on the optical recording of the movements of the neck by means of laser Doppler interferometry.
92 citations
TL;DR: The Arrhythmia monitoring system as mentioned in this paper collects real-time electrocardiogram signals from a mobile or homebound patient, and combines them with GPS location data, and transmits this information to a remote station for display and monitoring.
Abstract: We have developed and benchmarked real-time collection methods that exploit digital, packet-switched telephony services available in metropolitan areas. The Arrhythmia monitoring system collects real-time electrocardiogram signals from a mobile or homebound patient, and combines them with GPS location data, and transmits this information to a remote station for display and monitoring.
92 citations
TL;DR: Spectral analysis of the HRV signal and of the respiration signal indicated a higher respiration regularity during deep sleep, and a higher parasympathetic drive was confirmed by an increase in the coherence between theHRV and the resppiration signal in the HF band during NREM sleep.
Abstract: Sleep is a complex state characterized by important changes in the autonomic modulation of the cardiovascular activity. Heart rate variability (HRV) greatly changes during different sleep stages, showing a predominant parasympathetic drive to the heart during non-rapid eye movement sleep (NREM) and an increased sympathetic activity during rapid eye movement sleep (REM). Respiration undergoes important modifications as well, becoming deeper and more regular with deep sleep and shallower and more frequent during REM. The aim of the present study is to assess both autonomic cardiac regulation and cardiopulmonary coupling variations during different sleep stages in healthy subjects, using spectral and cross-spectral analysis of the HRV and respiration signals. Polysomnographic sleep recordings were performed in 11 healthy women and the HRV signal and the respiration signal were obtained. The spectral and cross-spectral parameters of the HRV signal and of the respiration signal were computed at low frequency (LF) and at breathing frequency (high frequency, HF) during different sleep stages. Results attested a sympatho-vagal balance shift towards parasympathetic modulation during NREM sleep and towards sympathetic modulation during REM sleep. Spectral analysis of the HRV signal and of the respiration signal indicated a higher respiration regularity during deep sleep, and a higher parasympathetic drive is also confirmed by an increase in the coherence between the HRV and the respiration signal in the HF band during NREM sleep. Our findings about sleep stage-dependent variations in the HRV signal and in the respiratory activity are in line with previous evidences and confirm spectral analysis of the HRV and the respiration signal to be a suitable tool for investigating cardiac autonomic modulation and respiration activity during sleep.
91 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...Peaks were detected from the ECG through the Pan–Tompkins algorithm (Pan and Tompkins, 1985), which reliably recognizes QRS complexes based upon the analyses of the signal slope, amplitude, and width....
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TL;DR: The increased heart rate and decreased heart rate variability in CRPS suggest a general autonomic imbalance, which is an independent predictor for increased mortality and sudden death.
Abstract: Background: Complex regional pain syndrome (CRPS) is a painconditionwithregionalsensoryandautonomicabnormalities in the affected limb. The authors studied systemic autonomic and hemodynamic function in CRPS patients during rest, and during orthostatic and mental arithmetic stress. Methods: Twenty patients with CRPS and 20 age-, sex-, and body mass index-matched control subjects participated. Meanvaluesofheartratevariability,baroreceptorsensitivity, blood pressure, stroke volume, cardiac output, and total peripheral resistance were estimated during supine rest and 60° tilt-table testing. On a separate day, heart rate variability was also measured during mental arithmetic stress testing induced by a paced auditory serial addition task. Results: Heart rate was increased and heart rate variability reduced in patients with CRPS patients compared with control subjects during rest and mental and orthostatic stress, whereas baroreceptor sensitivity was unaffected. When tilted from supine to upright position, patients with CRPS were not able to preserve cardiac output in comparison with control subjects, and they exhibited an exaggerated increase in the total peripheral resistance. The hemodynamic changes correlated to pain duration but not to pain intensity. Conclusion: The increased heart rate and decreased heart rate variability in CRPS suggest a general autonomic imbalance, which is an independent predictor for increased mortality and sudden death. The inability of the patients to protect their cardiac output during orthostatic stress was aggravated with the chronicity of the disease.
91 citations
TL;DR: A personalized health monitoring system that can detect early occurrences of arrhythmias from an individual’s electrocardiogram (ECG) signal using a Convolutional Neural Network trained using real normal and synthesized abnormal beats.
Abstract: Each year more than 7 million people die from cardiac arrhythmias. Yet no robust solution exists today to detect such heart anomalies right at the moment they occur. The purpose of this study was to design a personalized health monitoring system that can detect early occurrences of arrhythmias from an individual’s electrocardiogram (ECG) signal. We first modelled the common causes of arrhythmias in the signal domain as a degradation of normal ECG beats to abnormal beats. Using the degradation models, we performed abnormal beat synthesis which created potential abnormal beats from the average normal beat of the individual. Finally, a Convolutional Neural Network (CNN) was trained using real normal and synthesized abnormal beats. As a personalized classifier, the trained CNN can monitor ECG beats in real time for arrhythmia detection. Over 34 patients’ ECG records with a total of 63,341 ECG beats from the MIT-BIH arrhythmia benchmark database, we have shown that the probability of detecting one or more abnormal ECG beats among the first three occurrences is higher than 99.4% with a very low false-alarm rate.
91 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