Literature DB >> 28222005

A Modular Low-Complexity ECG Delineation Algorithm for Real-Time Embedded Systems.

Jose Manuel Bote, Joaquin Recas, Francisco Rincon, David Atienza, Roman Hermida.   

Abstract

This work presents a new modular and low-complexity algorithm for the delineation of the different ECG waves (QRS, P and T peaks, onsets, and end). Involving a reduced number of operations per second and having a small memory footprint, this algorithm is intended to perform real-time delineation on resource-constrained embedded systems. The modular design allows the algorithm to automatically adjust the delineation quality in runtime to a wide range of modes and sampling rates, from a ultralow-power mode when no arrhythmia is detected, in which the ECG is sampled at low frequency, to a complete high-accuracy delineation mode, in which the ECG is sampled at high frequency and all the ECG fiducial points are detected, in the case of arrhythmia. The delineation algorithm has been adjusted using the QT database, providing very high sensitivity and positive predictivity, and validated with the MIT database. The errors in the delineation of all the fiducial points are below the tolerances given by the Common Standards for Electrocardiography Committee in the high-accuracy mode, except for the P wave onset, for which the algorithm is above the agreed tolerances by only a fraction of the sample duration. The computational load for the ultralow-power 8-MHz TI MSP430 series microcontroller ranges from 0.2% to 8.5% according to the mode used.

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Year:  2017        PMID: 28222005     DOI: 10.1109/JBHI.2017.2671443

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  4 in total

1.  High Precision Digitization of Paper-Based ECG Records: A Step Toward Machine Learning.

Authors:  Mohammed Baydoun; Lise Safatly; Ossama K Abou Hassan; Hassan Ghaziri; Ali El Hajj; Hussain Isma'eel
Journal:  IEEE J Transl Eng Health Med       Date:  2019-11-07       Impact factor: 3.316

2.  An Accurate QRS complex and P wave Detection in ECG Signals using Complete Ensemble Empirical Mode Decomposition Approach.

Authors:  Billal Hossain; Syed Khairul Bashar; Allan J Walkey; David D McManus; Ki H Chon
Journal:  IEEE Access       Date:  2019-09-06       Impact factor: 3.367

3.  Toward ECG-based analysis of hypertrophic cardiomyopathy: a novel ECG segmentation method for handling abnormalities.

Authors:  Kasra Nezamabadi; Jacob Mayfield; Pengyuan Li; Gabriela V Greenland; Sebastian Rodriguez; Bahadir Simsek; Parvin Mousavi; Hagit Shatkay; M Roselle Abraham
Journal:  J Am Med Inform Assoc       Date:  2022-10-07       Impact factor: 7.942

4.  Sequence to Sequence ECG Cardiac Rhythm Classification Using Convolutional Recurrent Neural Networks.

Authors:  Teeranan Pokaprakarn; Rebecca R Kitzmiller; J Randall Moorman; Doug E Lake; Ashok K Krishnamurthy; Michael R Kosorok
Journal:  IEEE J Biomed Health Inform       Date:  2022-02-04       Impact factor: 7.021

  4 in total

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