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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TL;DR: A system that monitors two of the most vital physiological parameters integrated in a wearable textile garment with newborns suffering from an elevated risk for Sudden Infant Death Syndrome and the use of accelerometers enables a safe and hermetic packaging technique that excludes unwanted interference.
Abstract: A system is presented that monitors two of the most vital physiological parameters integrated in a wearable textile garment. Emphasis is put on the selection of sensing systems that are mechanically robust to suit the use in clothing. One application is with newborns suffering from an elevated risk for Sudden Infant Death Syndrome (SIDS). Heart and breathing rate are measured by sensing systems implemented on flexible substrates, integrated onto textile. Breathing rate is assessed by extracting accelerometer signals, which can also be used to detect the posture of the baby. The accelerometers have an accuracy of 1 mg and consume less than 2 mA, interface circuit included. Heart rate is assessed through ECG measurement with dry electrodes and a three-stage differential amplifier with a CMRR of 106 dB at 50 Hz. The system operates on a flexible 3.7 V battery and sends its acquired data wirelessly (at 2.4 GHz with a bandwidth of 770 Hz) to a computer, which processes and visualises the two parameters. Processing involves filtering and peak detection algorithms to extract the breathing and heart rate in Matlab. Because the presented work focuses on the two most important vital signs, the system already proves more robust than common home monitoring SIDS applications, typically focusing on a single parameter. Moreover, the use of accelerometers enables a safe and hermetic packaging technique that excludes unwanted interference.
33 citations
TL;DR: The results show an increased heart and respiratory rate during stress and attention, compared to a resting condition and a fast reduction in vagal activity, demonstrating that the autonomic response to mental stress is driven by mechanisms characterized by different temporal scales.
Abstract: Mental stress is a growing problem in our society. In order to deal with this, it is important to understand the underlying stress mechanisms. In this study, we aim to determine how the cardiorespiratory interactions are affected by mental arithmetic stress and attention. We conduct cross time-frequency (TF) analyses to assess the cardiorespiratory coupling. In addition, we introduce partial TF spectra to separate variations in the RR interval series that are linearly related to respiration from RR interval variations (RRV) that are not related to respiration. The performance of partial spectra is evaluated in two simulation studies. Time-varying parameters, such as instantaneous powers and frequencies, are derived from the computed spectra. Statistical analysis is carried out continuously in time to evaluate the dynamic response to mental stress and attention. The results show an increased heart and respiratory rate during stress and attention, compared to a resting condition. Also a fast reduction in vagal activity is noted. The partial TF analysis reveals a faster reduction of RRV power related to (3 s) than unrelated to (30 s) respiration, demonstrating that the autonomic response to mental stress is driven by mechanisms characterized by different temporal scales.
33 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...The RR interval series, the signal that contains the time between two heart beats, is composed by detection of the R peaks in the ECG using the Pan-Tompkins algorithm [30]....
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TL;DR: The aim of this work is to design a reliable algorithm for the identification and the classification of heart sounds’ main components and it was found capable of correctly detecting and classifying an average of 99.2% of the heart sounds along with their components.
Abstract: The auscultation of heart sounds has been for decades a fundamental diagnostic tool in clinical practice. Higher effectiveness can be achieved by recording the corresponding biomedical signal, namely the phonocardiographic signal, and processing it by means of traditional signal processing techniques. An unavoidable processing step is the heart sound segmentation, which is still a challenging task from a technical viewpoint—a limitation of state-of-the-art approaches is the unavailability of trustworthy techniques for the detection of heart sound components. The aim of this work is to design a reliable algorithm for the identification and the classification of heart sounds’ main components. The proposed methodology was tested on a sample population of 24 healthy subjects over 10-min-long simultaneous electrocardiographic and phonocardiographic recordings and it was found capable of correctly detecting and classifying an average of 99.2% of the heart sounds along with their components. Moreover, the delay of each component with respect to the corresponding R-wave peak and the delay among the components of the same heart sound were computed: the resulting experimental values are coherent with what is expected from the literature and what was obtained by other studies.
33 citations
Cites background or methods from "A Real-Time QRS Detection Algorithm..."
...Peaks are detected on the resulting pulse-shaped signal through decision rules based on a double-step thresholding process aimed at increasing the algorithm sensitivity [27]....
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...Peaks are detect d o the resulti pulse-shap d signal through decision ru s based on a double-st p thresholding pro ss aimed a incre sing the al orithm sensitivity [27]....
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...A modified version of Pan-Tompkins algorithm [27] is then applied to the filtered ECG....
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...This band was chosen because it contains the main frequency components of the QRS-complex [27]....
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TL;DR: In this paper, a signal quality modified Kalman filter was used to track blood pressure changes, which achieved higher measurement accuracy compared with straightforward use of the Pulse Arrival Time (PAT) based linear regression model.
Abstract: The present study designs an algorithm to increase the accuracy of continuous blood pressure (BP) estimation. Pulse arrival time (PAT) has been widely used for continuous BP estimation. However, because of motion artifact and physiological activities, PAT-based methods are often troubled with low BP estimation accuracy. This paper used a signal quality modified Kalman filter to track blood pressure changes. A Kalman filter guarantees that BP estimation value is optimal in the sense of minimizing the mean square error. We propose a joint signal quality indice to adjust the measurement noise covariance, pushing the Kalman filter to weigh more heavily on measurements from cleaner data. Twenty 2 h physiological data segments selected from the MIMIC II database were used to evaluate the performance. Compared with straightforward use of the PAT-based linear regression model, the proposed model achieved higher measurement accuracy. Due to low computation complexity, the proposed algorithm can be easily transplanted into wearable sensor devices.
33 citations
TL;DR: The conclusion is that the first and second HEP components are significant parameters that can quantitatively evaluate 3D visual fatigue and indicate that sensory input from 3D video requires heavy computation by the brain, stimulating heart activity.
33 citations
Cites methods from "A Real-Time QRS Detection Algorithm..."
...(1) The R-peak was detected in the ECG signal based on the QRS detection algorithm (Pan and Tompkins, 1985)....
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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