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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: The proposed alarm gating system successfully gated false alarms with future work exploring the misidentification of fiducial points by myocardial ischemia monitoring systems will decrease the incidence of the alarm fatigue condition typically found in clinicians.
Abstract: Objective : The objective of this study is to propose and validate an alarm gating system for a myocardial ischemia monitoring system that uses ambulatory electrocardiogram. The PeriOperative ISchemic Evaluation study recommended the selective administration of β blockers to patients at risk of cardiac events following noncardiac surgery. Patients at risk are identified by monitoring ST segment deviations in the electrocardiogram (ECG); however, patients are encouraged to ambulate to improve recovery, which deteriorates the signal quality of the ECG leading to false alarms. Methods : The proposed alarm gating system computes a signal quality index (SQI) to quantify the ECG signal quality and rejects alarms with a low SQI. The system was validated by artificially contaminating ECG records with motion artifact records obtained from the long-term ST database and MIT-BIH noise stress test database, respectively. Results : Without alarm gating, the myocardial ischemia monitoring system attained a Precision of 0.31 and a Recall of 0.78. The alarm gating improved the Precision to 0.58 with a reduction of Recall to 0.77. Conclusion : The proposed system successfully gated false alarms with future work exploring the misidentification of fiducial points by myocardial ischemia monitoring systems. Significance: The reduction of false alarms due to the proposed system will decrease the incidence of the alarm fatigue condition typically found in clinicians. Alarm fatigue condition was rated as the top patient safety hazard from 2012 to 2015 by the Emergency Care Research Institute.

40 citations


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

  • ...The R peaks were identified using the Complete Pan Tompkins Implementation ECG QRS detector toolbox available on MATLAB File Exchange [32], [33]....

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Journal ArticleDOI
TL;DR: The results support the conclusion that proposed ICA pre-processing can effectively improve the HR and HRV assessment from iPPG.
Abstract: Unobtrusive monitoring of vital signs is relevant for both medical (patient monitoring) and non-medical applications (e.g., stress and fatigue monitoring). In this paper, we focus on the use of imaging photoplethysmography (iPPG). High frame rate videos were acquired by using a monochrome camera and an optical band-pass filter ( $\text{560}\pm \text{20}$ nm). To enhance iPPG signal, we investigated the use of independent component analysis (ICA) pre-processing applied to iPPG signal from different regions of the face. Methodology was tested on $\text{30}$ healthy volunteers. Heart rate (HR) and standard time and frequency domain descriptors of heart rate variability (HRV), simultaneously extracted from videos and ECG data, were compared. A mean absolute error (MAE) about 3.812 ms was observed for normal-to-normal intervals with or without ICA pre-processing. Smaller MAE values of frequency domain descriptors were observed when ICA pre-processing was used. The impact of both video frame rate and video signal interval were also analyzed. All the results support the conclusion that proposed ICA pre-processing can effectively improve the HR and HRV assessment from iPPG.

40 citations


Additional excerpts

  • ...were defined following QRS complex detection [38]....

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DissertationDOI
01 Jan 2011
TL;DR: The goal of this thesis is to investigate novel non‐invasive technologies for the continuous measurement of BP, with particular emphasis on non‐occlusive technologies that can be used in ambulatory scenarios, during daily life activities and not only within hospitals or physicians' offices.
Abstract: Elevated Blood Pressure (BP) is a human‐specific illness affecting a quarter of the worldwide population. Clinically known as hypertension, elevated BP is considered the major risk factor for cardiovascular disease: the most common cause of death in developed countries. Detecting, treating and controlling hypertension are major goals of modern medicine. For more than one century, the non‐invasive measurement of BP has relied on the inflation of pneumatic cuffs around a limb, typically the upper arm. In addition to being occlusive, and thus cumbersome, clinical cuff‐based methods provide intermittent BP readings, i.e. every twenty minutes, hence impeding the suitable monitoring of short‐term BP regulation mechanisms. In addition, cuff‐based methods may not yield representative BP during sleep as repeated inflations induce arousal reactions, leading to non‐representative overestimated BP values. Therefore, the development of novel technologies that reduce the recurrent use of pneumatic cuffs is clearly justified. The goal of this thesis is to investigate novel non‐invasive technologies for the continuous measurement of BP. Particular emphasis is given to non‐occlusive technologies that can be used in ambulatory scenarios, during daily life activities and not only within hospitals or physicians' offices. This thesis addresses thus the challenge of ambulatory BP monitoring from four different perspectives: cardiovascular physiology, clinical applicability, system integration, and signal/information processing. The thesis starts by reviewing basic concepts of cardiovascular physiology related to the control of BP in humans: this analysis aims at setting the background knowledge for the understanding of the challenges faced by the BP monitoring field. Currently existing approaches for the non‐invasive monitoring of BP are then reviewed systematically: their principles of work and their respective advantages/limitations are identified from both, clinical and ambulatory perspectives. The studied approaches are the auscultatory, oscillometric, tonometric, volume‐clamp and pulse wave velocity techniques. The introductory part of this thesis is completed with a comprehensive review of the metrological means for the non‐invasive and non‐occlusive monitoring of cardiovascular parameters that have been used for this research, namely: electro‐cardiography (ECG), photo‐plethysmography (PPG), phono‐cardiography (PCG), impedance‐cardiography (ICG) and electrical impedance tomography (EIT). The thorough appraisal of the state of the art identifies the Pulse Wave Velocity (PWV) technique as the most promising track to follow, since it provides the best trade‐off between clinical and ambulatory compliances. PWV‐based techniques rely on the fact that the velocity at which arterial pressure pulses propagate along the arterial tree depends on the underlying BP. Therefore, by continuously measuring PWV …

40 citations

Journal ArticleDOI
TL;DR: The concept of AI and some of the requisites of machine learning and deep learning are described and the use of AI for battling the novel severe acute respiratory syndrome-coronavirus-2 pandemic is reviewed.
Abstract: Artificial intelligence (AI) is transforming healthcare delivery. The digital revolution in medicine and healthcare information is prompting a staggering growth of data intertwined with elements from many digital sources such as genomics, medical imaging and electronic health records. Such massive growth has sparked the development of an increasing number of AI-based applications that can be deployed in clinical practice. Pulmonary specialists who are familiar with the principles of AI and its applications will be empowered and prepared to seize future practice and research opportunities. The goal of this review is to provide pulmonary specialists and other readers with information pertinent to the use of AI in pulmonary medicine. First, we describe the concept of AI and some of the requisites of machine learning and deep learning. Next, we review some of the literature relevant to the use of computer vision in medical imaging, predictive modelling with machine learning, and the use of AI for battling the novel severe acute respiratory syndrome-coronavirus-2 pandemic. We close our review with a discussion of limitations and challenges pertaining to the further incorporation of AI into clinical pulmonary practice.

40 citations

Journal ArticleDOI
TL;DR: A loop-locked framework integrating AF diagnose, label query, and model fine-tuning is proposed integrating MIDNN model and the suitability of novel learning strategy for AF and can be extended to other biomedical applications.

40 citations

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