A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles

Homaeinezhad, Mohammad Reza; Erfanianmoshiri-Nejad, M.; Naseri, H.

doi:10.1016/j.compbiomed.2013.10.024

Cited by 37 publications

(18 citation statements)

References 31 publications

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“…If white noise is added to the continuous model of a system, a random‐walks noise appears in the corresponding discrete model of system. This behavior is coincident with the noise model of real applications .…”

Section: Simulation Studysupporting

confidence: 78%

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

Homaeinezhad¹,

Moghaddam²,

Khakpour³

et al. 2015

Asian Journal of Control

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The precision of a closed‐loop controller system designed for an uncertain plant depends strongly upon the maximum extent to which it is possible to track the trend of time‐varying parameters of the plant. The aim of this study is to describe a new parameter estimation algorithm that is able to follow fast‐varying parameters in closed‐loop systems. The short‐time linear quadratic form (STLQF) estimation algorithm introduced in this paper is a technique for tracking time‐varying parameters based on short‐time analysis of the regressing variables in order to minimize locally a linear quadratic form cost function. The established cost function produces a linear combination of errors with several delays. To meet this objective, mathematical development of the STLQF estimation algorithm is described. To implement the STLQF algorithm, the algorithm is applied to a planar mobile robot with fast‐varying parameters of inertia and viscous and coulomb frictions. Next, performance of the proposed algorithm is assessed against noise effects and variation in the type of parameters.

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Section: Simulation Studysupporting

confidence: 78%

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

Homaeinezhad¹,

Moghaddam²,

Khakpour³

et al. 2015

Asian Journal of Control

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“…Although more recent approaches for this purpose can be found in the literature (e.g. [18,19]), the algorithm used here provided high accuracy and very few location errors [17]. Moreover, it is worth noting that automatic P-wave delineation allows to obtain highly reproducible measurements [20].…”

Section: P-wave Delineation and Characterisationmentioning

confidence: 96%

Alteration of the P-wave non-linear dynamics near the onset of paroxysmal atrial fibrillation

Martínez

Abásolo

Alcaraz

et al. 2015

Medical Engineering & Physics

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“…In this procedure, several probes are placed in certain positions to define places in a bare chest [9], [10]. These probes generate electrical current as a result of measuring the electrical activity of each heartbeat on the surface of the chest [11], [12].…”

Section: Introductionmentioning

confidence: 99%

ECG Waveform Classification Based on P-QRS-T Wave Recognition

Al-Ani

2018

UHD J SCI TECH

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A B S T R A C TElectrocardiogram (ECG) is a periodic signal reflects the activity of the heart. ECG waveform is an important issue to define the heart function, so it is helpful to recognize the type of heart diseases. ECG graph generates a lot of information that is converted into an electrical signal with standard values of amplitude and duration. The main problem raised in this measurement is the mixing between normal and abnormal, in addition, sometimes, there are overlapping between the P-QRS-T waveform. This research aims to offer an efficient approach to measure all parts of P-QRS-T waveform in order to give a correct decision of heart functionality. The implemented approach including many steps as follows: Preprocessing, baseline process, feature extraction, and diagnosis. The obtained result indicated an adequate recognition rate to verify the heart functionality. The proposed approach depends mainly on the classifier process that based mainly on the extracted ECG waveform features that achieved from exact baseline detection.

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A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles

Cited by 37 publications

References 31 publications

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

Alteration of the P-wave non-linear dynamics near the onset of paroxysmal atrial fibrillation

ECG Waveform Classification Based on P-QRS-T Wave Recognition

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