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A Real-Time QRS Detection Algorithm

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TLDR
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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Journal ArticleDOI

Automated detection of atrial fibrillation using Bayesian paradigm

TL;DR: A methodology for ECG based pattern analysis of normal sinus rhythm and atrial fibrillation (AF) beats is presented and the probability of error during classification was less for GMM compared to Naive Bayes classifier (NBC) as GMM provided higher performance than the NBC.
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A deep learning approach for fetal QRS complex detection

TL;DR: A deep learning approach for fetal QRS complex detection from raw NI-FECG signals by using a convolutional neural network (CNN) model is proposed and results show that Relu outperforms the Sigmoid and Tanh on this particular task, and better classification performance is obtained with the signal quality assessment step in this study.
Journal ArticleDOI

An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm.

TL;DR: An adaptive and time-efficient R-peak detection algorithm for ECG processing was proposed using wavelet multiresolution analysis to enhance the ECG signal representation and local maximums were calculated by the first-order forward differential approach to locate the R-peaks.
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Heart Rate Variability (HRV) and Pulse Rate Variability (PRV) for the Assessment of Autonomic Responses

TL;DR: Investigating the differences between HRV and PRV found that PRV responds to cold exposure differently to HRV, especially in peripheral sites such as the finger and the toe, and may have different information not available in HRV due to its non-localized nature.
Journal ArticleDOI

MR-based respiratory and cardiac motion correction for PET imaging

TL;DR: The proposed method provides a clinically feasible setup for respiratory and cardiac motion correction of PET data by simultaneous short‐term MRI using simultaneously acquired magnetic‐resonance (MR) images within 90 s.
References
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Journal ArticleDOI

Software QRS detection in ambulatory monitoring--a review.

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.
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Optimal QRS detector.

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.
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Automated High-Speed Analysis of Holter Tapes with Microcomputers

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.
Journal ArticleDOI

Online digital filters for biological signals: some fast designs for a small computer.

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.
Journal ArticleDOI

A robust-digital QRS-detection algorithm for arrhythmia monitoring

TL;DR: In this paper a new robust single lead QRS-detection algorithm is presented, allowing real-time applications and results are presented.
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