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 novel multi-lead attention (MLA) mechanism integrated with convolutional neural network (CNN) and bidirectional gated recurrent unit (BiGRU) framework is proposed to detect and locate MI via 12-lead ECG records.
Abstract: The electrocardiogram (ECG) is a non-invasive, inexpensive, and effective tool for myocardial infarction (MI) diagnosis. Conventional detection algorithms require solid domain expertise and rely heavily on handcrafted features. Although previous works have studied deep learning methods for extracting features, these methods still neglect the relationships between different leads and the temporal characteristics of ECG signals. To handle the issues, a novel multi-lead attention (MLA) mechanism integrated with convolutional neural network (CNN) and bidirectional gated recurrent unit (BiGRU) framework (MLA-CNN-BiGRU) is therefore proposed to detect and locate MI via 12-lead ECG records. Specifically, the MLA mechanism automatically measures and assigns the weights to different leads according to their contribution. The two-dimensional CNN module exploits the interrelated characteristics between leads and extracts discriminative spatial features. Moreover, the BiGRU module extracts essential temporal features inside each lead. The spatial and temporal features from these two modules are fused together as global features for classification. In experiments, MI location and detection were performed under both intra-patient scheme and inter-patient scheme to test the robustness of the proposed framework. Experimental results indicate that our intelligent framework achieved satisfactory performance and demonstrated vital clinical significance.
55 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...Additionally, Pan–Tompkin algorithm [45] was employed to segment or select the pre-processed ECG signals by QRS-wave detection....
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TL;DR: The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system.
Abstract: Body area sensor networks (BANs) utilize wireless communicating sensor nodes attached to a human body for convenience, safety, and health applications. Physiological characteristics of the body, such as the heart rate or Electrocardiogram (ECG) signals, are promising means to simplify the setup process and to improve security of BANs. This paper describes the design and implementation steps required to realize an ECG-based authentication protocol to identify sensor nodes attached to the same human body. Therefore, the first part of the paper addresses the design of a body-area sensor system, including the hardware setup, analogue and digital signal processing, and required ECG feature detection techniques. A model-based design flow is applied, and strengths and limitations of each design step are discussed. Real-world measured data originating from the implemented sensor system are then used to set up and parametrize a novel physiological authentication protocol for BANs. The authentication protocol utilizes statistical properties of expected and detected deviations to limit the number of false positive and false negative authentication attempts. The result of the described holistic design effort is the first practical implementation of biometric authentication in BANs that reflects timing and data uncertainties in the physical and cyber parts of the system.
54 citations
Cites background or methods from "A Real-Time QRS Detection Algorithm..."
...The benefit of PTA is that each step can easily be implemented even on severely constrained embedded devices....
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...Filter Implementation in C One of the most utilized functions in the data process flow is Matlab’s filter function (filtfilt). filtfilt is used for digital filtering of the input data and for various steps of the PTA....
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...Algorithm 1 Model-based Validation on detected QRS peaks Input: arrays Q, R, S time and values . size of arrays might differ, may contain invalid values WindowSize = 0.1 s Output: arrays Q’, R’, S’ time and values . size(Q) = size(R) = size(S) 1: EndWindowTime = 0; 2: for all rpeak ∈ R : time(rpeak) > EndWindowTime do 3: StartWindowTime = time(rpeak)−WindowSize/2 4: EndWindowTime = time(rpeak) + WindowSize/2 5: idR = idQ = idS = 0 . pointer to identified Q,R,S 6: for all r ∈ R : StartWindowTime ≤ time(r) ≤ EndWindowTime do 7: if idR = 0 ∨ value(r) > value(idR) then idR = r 8: for all q ∈ Q : StartWindowTime ≤ time(q) ≤ time(idR) do 9: if idQ = 0 ∨ value(q) < value(idQ) then idQ = q 10: for all s ∈ S : time(idR) ≤ time(s) ≤ EndWindowTime do 11: if idS = 0 ∨ value(s) < value(idS) then idS = s 12: if idQ 6= 0∧ idR 6= 0∧ idS 6= 0 then 13: Q′+ = idQ; R′+ = idR; S′+ = idS; 14: return Q′, R′, S′ The inputs to the validation algorithm are the Q, R, and S locations (time, value) delivered by PTA....
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...PTA performs a sequence of filtering and comparison steps, including: • a five-point derivative filtering to provide the slope information of the QRS complex, using the transfer function H(z) = 18 (−z−2 − 2z−1 + 2z1 + z2), • squaring of the signal, to obtain all positive signal values and nonlinear amplification to emphasize the characteristic higher ECG frequencies, • fixed moving window integration to obtain waveform feature information in addition to the slope of the R wave, and • a comparison step to identify the largest peaks in a window to locate Q, R, and S....
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...PTA is also considered as robust in presence of abnormal ECGs, such as arrhytmias [37]....
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TL;DR: Both WT6 and WT7 have been proved to be superior in performance to the existing wavelets and holds high promise for error-free reliable QRS detection in computer-aided feature extraction and disease diagnostics.
Abstract: This paper deals with a new wavelet (WT) which has been developed and very effectively and efficiently used for the detection of QRS segments from the ECG signal. After carrying out the detection using five existing wavelets (two symmetric-- WT1 and WT2--and three asymmetric--WT3, WT4 and WT5), two new wavelets (WT6 and WT7) were constructed and used for QRS detection. WT6 is a symmetric wavelet and has been constructed by a trial-and-error method. WT7 is an adaptive symmetric wavelet and adjusts its threshold as per the amplitude of the ECG signal. The accuracy of QRS detection obtained from WT6 is 99.8% and from WT7 100%. The CSE DS-3 database has been used for tests. Both WT6 and WT7 have been proved to be superior in performance to the existing wavelets. Out of WT6 and WT7, WT7 holds high promise for error-free reliable QRS detection in computer-aided feature extraction and disease diagnostics.
54 citations
TL;DR: Increased autonomic arousal (heart rate, skin conductance and blood pressure) and psychophysiological (ERP) data acquired during the working memory task found supported an increase in performance and underlying brain function with methylphenidate.
Abstract: The effects of methylphenidate (MPH) on 32 healthy human male volunteers (aged 18 to 25 years, mean age=22.26) were examined using a within-subject design. Each participant attended six testing periods, held once per week. Within each testing period, three repeat testing sessions were undertaken: pre-medication, on-medication and two hours post-medication. In these sessions, dose was manipulated (placebo, 5 mg, 15 mg or 45 mg) according a double-blind placebo design. In this report, we focus on behavioral, autonomic arousal (heart rate, skin conductance) and psychophysiological (ERP) data acquired during the working memory task. We found increased autonomic arousal (heart rate, skin conductance and blood pressure) with MPH. A linear reduction in reaction time, omission errors and target P3 latency, and a corresponding increase in background P3 amplitude was observed with increased MPH dose. The relationship between these measures supported an increase in performance and underlying brain function with MPH. To our knowledge, this is the first paper to use behavioral, arousal and electrophysiological measures in an integrative approach to study the effects of MPH on healthy adults.
54 citations
TL;DR: LZMA based ECG data compression technique is proposed, which achieves the highest signal to noise ratio, and lowest root mean square error, and is capable of distinguishing accurately between healthy, myocardial infarction, congestive heart failure and coronary artery disease patients.
Abstract: Heart rate monitoring and therapeutic devices include real-time sensing capabilities reflecting the state of the heart. Current circuitry can be interpreted as a cardiac electrical signal compression algorithm representing the time signal information into a single event description of the cardiac activity. It is observed that some detection techniques developed for ECG signal detection like artificial neural network, genetic algorithm, Hilbert transform, hidden Markov model are some sophisticated algorithms which provide suitable results but their implementation on a silicon chip is very complicated. Due to less complexity and high performance, wavelet transform based approaches are widely used. In this paper, after a thorough analysis of various wavelet transforms, it is found that Biorthogonal wavelet transform is best suited to detect ECG signal's QRS complex. The main steps involved in ECG detection process consist of de-noising and locating different ECG peaks using adaptive slope prediction thresholding. Furthermore, the significant challenges involved in the wireless transmission of ECG data are data conversion and power consumption. As medical regulatory boards demand a lossless compression technique, lossless compression technique with a high bit compression ratio is highly required. Furthermore, in this work, LZMA based ECG data compression technique is proposed. The proposed methodology achieves the highest signal to noise ratio, and lowest root mean square error. Also, the proposed ECG detection technique is capable of distinguishing accurately between healthy, myocardial infarction, congestive heart failure and coronary artery disease patients with a detection accuracy, sensitivity, specificity, and error of 99.92%, 99.94%, 99.92% and 0.0013, respectively. The use of LZMA data compression of ECG data achieves a high compression ratio of 18.84. The advantages and effectiveness of the proposed algorithm are verified by comparing with the existing methods.
54 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