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 present study aims at developing a pulsatile control algorithm for rotary pumps to investigate the impact of pump speed modulation during systole and diastole on the left ventricle unloading and is an initial step to more accurate speed modulation of RBPs to optimize the cardiac load control.
Abstract: OBJECTIVES: Rotary blood pumps (RBPs) running at a constant speed are routinely used for the mechanical support of the heart in various clinical applications, from short-term use in heart-lung machines to long-term support of a failing heart. Their operating range is delineated by suction and regurgitation events, leaving limited control on the cardiac workload. This study investigates whether different ratios of systolic/diastolic support are advantageous over a constant-speed operation. METHODS: In order to effectively control the load on the heart, this study aimed at developing a pulsatile control algorithm for rotary pumps to investigate the impact of pump speed modulation during systole and diastole on the left ventricle unloading. The CentriMag TM RBP with a modified controller was implanted in four sheep via a left thoracotomy and cannulated from the ventricular apex to the descending aorta. To modulate the pump speed synchronized with the heartbeat, custom-made real-time software detected the QRS complex of the electrocardiogram and controlled the pump speed during systole and diastole. Four different speed modulations with the same average speed but different systolic and diastolic speeds were compared with the baseline and the constant speed support. Left ventricular (LV) pressure and volume, coronary flow and pump flow were analysed to examine the influence of the pump speed modulation. RESULTS: Pulsatile setting reduces the cardiac workload to 64% of the baseline and 72% of the constant speed value. Maximum unloading is obtained with the highest speed during diastole and high-pulse amplitude. End-diastolic volume in the pulsatile modes varied from 85 to 94% of the baseline and 96 to 107% of the constant speed value. Consequently, the mechanical load on the heart can be adjusted to provide assuagement, which may lead to myocardial recovery. The higher pump speed during systole results in an increase in the pulse pressure up to 140% compared with the constant speed. CONCLUSIONS: The present study is an initial step to more accurate speed modulation of RBPs to optimize the cardiac load control. To develop future control algorithms, the concept of high speed during diastole having a maximal unloading effect on the LV and high speed during systole increasing the pulse pressure is worth considering.
45 citations
TL;DR: A proof of concept study which demonstrates for the first time the possibility of recording magnetocardiography (MCG) signals with 4He vector optically pumped magnetometers (OPM) operated in a gradiometer mode.
Abstract: In this paper, we present a proof of concept study which demonstrates for the first time the possibility of recording magnetocardiography (MCG) signals with 4He vector optically pumped magnetometers (OPM) operated in a gradiometer mode. Resulting from a compromise between sensitivity, size and operability in a clinical environment, the developed magnetometers are based on the parametric resonance of helium in a zero magnetic field. Sensors are operated at room temperature and provide a tri-axis vector measurement of the magnetic field. Measured sensitivity is around 210 f T (√Hz)−1 in the bandwidth (2 Hz; 300 Hz). MCG signals from a phantom and two healthy subjects are successfully recorded. Human MCG data obtained with the OPMs are compared to reference electrocardiogram recordings: similar heart rates, shapes of the main patterns of the cardiac cycle (P/T waves, QRS complex) and QRS widths are obtained with both techniques.
45 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...…the reference and OPM signals is performed through the detection of RR interval (heart rate) and QRS duration following Pan and Tompkins algorithm (Pan and Tompkins, 1985) (Elgendi, 2013): QRS enhancement is performed by pre-filtering the signal with a third order Butterworth bandpass filter in…...
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TL;DR: An algorithm that extracts short- and long-term energies in a signal and provides a coefficient vector with which the signal is multiplied, heightening events of interest, for robust short-term event extraction from biomedical signals.
Abstract: In this paper, we propose a fast novel nonlinear filtering method named Relative-Energy (Rel-En), for robust short-term event extraction from biomedical signals. We developed an algorithm that extracts short- and long-term energies in a signal and provides a coefficient vector with which the signal is multiplied, heightening events of interest. This algorithm is thoroughly assessed on benchmark datasets in three different biomedical applications, namely ECG QRS-complex detection, EEG K-complex detection, and imaging photoplethysmography (iPPG) peak detection. Rel-En successfully identified the events in these settings. Compared to the state-of-the-art, better or comparable results were obtained on QRS-complex and K-complex detection. For iPPG peak detection, the proposed method was used as a preprocessing step to a fixed threshold algorithm that lead to a significant improvement in overall results. While easily defined and computed, Rel-En robustly extracted short-term events of interest. The proposed algorithm can be implemented by two filters and its parameters can be selected easily and intuitively. Furthermore, Rel-En algorithm can be used in other biomedical signal processing applications where a need of short-term event extraction is present.
45 citations
01 Oct 2017
TL;DR: In this paper, a multi-task learning approach based on neural networks was proposed to account for individual differences in pain responses while still leveraging data from across the population, and the method was tested in a dataset containing multi-modal physiological responses to nociceptive pain.
Abstract: Pain is a complex and subjective experience that poses a number of measurement challenges. While self-report by the patient is viewed as the gold standard of pain assessment, this approach fails when patients cannot verbally communicate pain intensity or lack normal mental abilities. Here, we present a pain intensity measurement method based on physiological signals. Specifically, we implement a multi-task learning approach based on neural networks that accounts for individual differences in pain responses while still leveraging data from across the population. We test our method in a dataset containing multi-modal physiological responses to nociceptive pain.
45 citations
TL;DR: This work has proposed computer assisted diagnosis of CAD using Heart Rate (HR) signals obtained from Electrocardiogram (ECG) signals using the Empirical Mode Decomposition (EMD) technique.
Abstract: Coronary Artery Disease (CAD) is a heart disease caused due to insufficient supply of nutrients and oxygen to the heart muscles. Hence, reduced supply of nutrients and oxygen causes heart attack or stroke and may cause death. Also significant number of people are suffering from CAD around the world so timely diagnosis of CAD can save the life of patients. In this work, we have proposed computer assisted diagnosis of CAD using Heart Rate (HR) signals obtained from Electrocardiogram (ECG) signals. We have used the Empirical Mode Decomposition (EMD) technique to process the HR signals. The features namely: Second-Order Difference Plot (SODP) area, Analytic Signal Representation (ASR) area, Amplitude Modulation (AM) bandwidth, Frequency Modulation (FM) bandwidth and Fourier–Bessel expansion (FBE)- based mean frequency computed from the Intrinsic Mode Functions (IMFs) are extracted to discriminate normal and CAD subjects. Thereafter, Kruskal–Wallis statistical test is performed on these features. The features having p-value less than 0.05 are considered to be significant. Our results show that three features namely: AM bandwidth, FM bandwidth and FBE-based mean frequency are more suitable than ASR area and SODP area features for discrimination of normal and CAD subjects.
45 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