An Efficient Low Computational Cost Method of R-Peak Detection

Gupta, Varun; Mittal, M.; Mittal, Vikas

doi:10.1007/s11277-020-08017-3

Cited by 30 publications

(4 citation statements)

References 61 publications

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“…However, many methods for R peak detection have been used since the classical paper by Pan and Tompkins 49 . The different peak and feature detection techniques are helpful in many specific applications, such as wearable devices 50 , 51 , arrhythmia detection 52 , 53 , or other, as summarized e.g. by Gupta et al 54 .…”

Section: Methodsmentioning

confidence: 99%

Finite velocity of ECG signal propagation: preliminary theory, results of a pilot experiment and consequences for medical diagnosis

Buchner

Zajdel

Pęczalski

et al. 2023

Sci Rep

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A satisfactory model of the biopotentials propagating through the human body is essential for medical diagnostics, particularly for cardiovascular diseases. In our study, we develop the theory, that the propagation of biopotential of cardiac origin (ECG signal) may be treated as the propagation of low-frequency endogenous electromagnetic wave through the human body. We show that within this approach, the velocity of the ECG signal can be theoretically estimated, like for any other wave and physical medium, from the refraction index of the tissue in an appropriate frequency range. We confirm the theoretical predictions by the comparison with a direct measurement of the ECG signal propagation velocity and obtain mean velocity as low as v=1500 m/s. The results shed new light on our understanding of biopotential propagation through living tissue. This propagation depends on the frequency band of the signal and the transmittance of the tissue. This finding may improve the interpretation of the electric measurements, such as ECG and EEG when the frequency dependence of conductance and the phase shift introduced by the tissue is considered. We have shown, that the ECG propagation modifies the amplitude and phase of signal to a considerable extent. It may also improve the convergence of inverse problem in electrocardiographic imaging.

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Section: Methodsmentioning

confidence: 99%

Finite velocity of ECG signal propagation: preliminary theory, results of a pilot experiment and consequences for medical diagnosis

Buchner

Zajdel

Pęczalski

et al. 2023

Sci Rep

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“…Excellent current R-peak detection algorithms have achieved over 99% positive predictability and sensitivity [21][22][23][24][25][26][27][28], and here, we have used the classical Pan-Tompkins algorithm to determine the R position, as in Figure 2. The R-peak reference point is taken as a heartbeat of about 0.3 s ahead and about 0.4 s behind, about 250 points.…”

Section: Ecg Beat Segmentationmentioning

confidence: 99%

Identification of Arrhythmia by Using a Decision Tree and Gated Network Fusion Model

Zhang

Zhang³

et al. 2021

Computational and Mathematical Methods in Medicine

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In recent years, deep learning (DNN) based methods have made leapfrogging level breakthroughs in detecting cardiac arrhythmias as the cost effectiveness of arithmetic power, and data size has broken through the tipping point. However, the inability of these methods to provide a basis for modeling decisions limits clinicians’ confidence on such methods. In this paper, a Gate Recurrent Unit (GRU) and decision tree fusion model, referred to as (T-GRU), was designed to explore the problem of arrhythmia recognition and to improve the credibility of deep learning methods. The fusion model multipathway processing time-frequency domain featured the introduction of decision tree probability analysis of frequency domain features, the regularization of GRU model parameters and weight control to improve the decision tree model output weights. The MIT-BIH arrhythmia database was used for validation. Results showed that the low-frequency band features dominated the model prediction. The fusion model had an accuracy of 98.31%, sensitivity of 96.85%, specificity of 98.81%, and precision of 96.73%, indicating its high reliability and clinical significance.

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“…The operations are time-consuming and so avoiding them by getting the features directly from the signal [36], [37] without affecting the accuracy of classification [38]- [40] is crucial in case of emergency or when time is very important. This saves the time of the central processing unit and reduces computational time [41]. Bio-signals are usually measured in the time domain which contains a lot of data to process [42], [43].…”

Section: Introductionmentioning

confidence: 99%

Design and analysis of a new brake-by-wire system using machine learning

Hassanein

Dawod

Hassan

2023

IJECE

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One of the main aims of the recent research on brake-by-wire systems is to decrease mechanical components. In this paper, we propose replacing the brake pedal with a driving wheel that is fully covered by pressure braking batch sensors. The new mechanism for braking translates pressure exerted through the driver’s hands on the driving wheel to a corresponding electrical signal. A proposed design for the pressure braking batch (PBB) is made out of a mesh of conducting threads separated by a resistive sheet. To the best of our knowledge, this idea has not been raised before in other research papers. Different people have different muscle strengths and so the problem of identifying the intention of the user when pressing the PBB is tackled. For this aim, a new dataset of its kind is created by several volunteers. From each volunteer, age, gender, body mass index (BMI), and maximum pressure exerted on the driving wheel are collected. Using Weka software, the detection accuracy is calculated for a new volunteer to know the intention of his/her pressure on PBB. Among the three algorithms tried, the regression tree gives the best results in predicting the class of the pressure exerted by the volunteers.

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An Efficient Low Computational Cost Method of R-Peak Detection

Cited by 30 publications

References 61 publications

Finite velocity of ECG signal propagation: preliminary theory, results of a pilot experiment and consequences for medical diagnosis

Finite velocity of ECG signal propagation: preliminary theory, results of a pilot experiment and consequences for medical diagnosis

Identification of Arrhythmia by Using a Decision Tree and Gated Network Fusion Model

Design and analysis of a new brake-by-wire system using machine learning

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