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Journal ArticleDOI

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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A robust deep convolutional neural network for the classification of abnormal cardiac rhythm using single lead electrocardiograms of variable length

TL;DR: A robust deep learning-based architecture that can identify abnormal cardiac rhythms using short single-lead ECG recordings is presented and can also be used in real-time cardiac arrhythmia detection applications.
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An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

TL;DR: A novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.
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Ballistocardiogram artifact reduction in the simultaneous acquisition of auditory ERPS and fMRI.

TL;DR: It is concluded that through adequate reduction of the ballistocardiogram artifact, relatively small auditory ERPs can be acquired in the MR environment.
Proceedings ArticleDOI

A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons

TL;DR: All four algorithms show a fairly poor performance on healthy subjects' data and especially geriatric patients' data, and more research is needed to evaluate the accuracy of step detection methods on mobility-impaired subjects.
Proceedings ArticleDOI

Detection of Acute Stress by Heart Rate Variability Using a Prototype Mobile ECG Sensor

TL;DR: The feasibility of using a mobile ECG sensor to detect subtle changes in HRV features that may enable stress monitoring and management in daily life is shown.
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.
Journal ArticleDOI

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.
Journal ArticleDOI

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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