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Pubmed for Handhelds

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Journal Abstract Search

311 related items for PubMed ID: 29068369

  • 1. Arrhythmia Evaluation in Wearable ECG Devices.
    Sadrawi M, Lin CH, Lin YT, Hsieh Y, Kuo CC, Chien JC, Haraikawa K, Abbod MF, Shieh JS.
    Sensors (Basel); 2017 Oct 25; 17(11):. PubMed ID: 29068369
    [Abstract] [Full Text] [Related]

  • 2. Automatic classification of heartbeats using ECG morphology and heartbeat interval features.
    de Chazal P, O'Dwyer M, Reilly RB.
    IEEE Trans Biomed Eng; 2004 Jul 25; 51(7):1196-206. PubMed ID: 15248536
    [Abstract] [Full Text] [Related]

  • 3. Real-time arrhythmia detection with supplementary ECG quality and pulse wave monitoring for the reduction of false alarms in ICUs.
    Krasteva V, Jekova I, Leber R, Schmid R, Abächerli R.
    Physiol Meas; 2016 Aug 25; 37(8):1273-97. PubMed ID: 27454550
    [Abstract] [Full Text] [Related]

  • 4. Bidirectional Recurrent Neural Network And Convolutional Neural Network (BiRCNN) For ECG Beat Classification.
    Xie P, Wang G, Zhang C, Chen M, Yang H, Lv T, Sang Z, Zhang P.
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul 25; 2018():2555-2558. PubMed ID: 30440929
    [Abstract] [Full Text] [Related]

  • 5. [Heartbeat-based end-to-end classification of arrhythmias].
    Deng L, Fu R.
    Nan Fang Yi Ke Da Xue Xue Bao; 2019 Sep 30; 39(9):1071-1077. PubMed ID: 31640959
    [Abstract] [Full Text] [Related]

  • 6. An ECG Heartbeat Classification Method Based on Deep Convolutional Neural Network.
    Zhang D, Chen Y, Chen Y, Ye S, Cai W, Chen M.
    J Healthc Eng; 2021 Sep 30; 2021():7167891. PubMed ID: 34616536
    [Abstract] [Full Text] [Related]

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  • 9. Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals.
    Hajeb-Mohammadalipour S, Ahmadi M, Shahghadami R, Chon KH.
    Sensors (Basel); 2018 Jun 29; 18(7):. PubMed ID: 29966276
    [Abstract] [Full Text] [Related]

  • 10. Sequential algorithm for life threatening cardiac pathologies detection based on mean signal strength and EMD functions.
    Anas EM, Lee SY, Hasan MK.
    Biomed Eng Online; 2010 Sep 04; 9():43. PubMed ID: 20815909
    [Abstract] [Full Text] [Related]

  • 11. Deep Learning Based Patient-Specific Classification of Arrhythmia on ECG signal.
    Zhao W, Hu J, Jia D, Wang H, Li Z, Yan C, You T.
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul 04; 2019():1500-1503. PubMed ID: 31946178
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  • 13. A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors.
    Zhao Y, Shang Z, Lian Y.
    IEEE Trans Biomed Circuits Syst; 2020 Apr 04; 14(2):186-197. PubMed ID: 31794404
    [Abstract] [Full Text] [Related]

  • 14. Robust Heartbeat Classification for Wearable Single-Lead ECG via Extreme Gradient Boosting.
    Zhu H, Zhao Y, Pan Y, Xie H, Wu F, Huan R.
    Sensors (Basel); 2021 Aug 05; 21(16):. PubMed ID: 34450733
    [Abstract] [Full Text] [Related]

  • 15. An arrhythmia classification system based on the RR-interval signal.
    Tsipouras MG, Fotiadis DI, Sideris D.
    Artif Intell Med; 2005 Mar 05; 33(3):237-50. PubMed ID: 15811788
    [Abstract] [Full Text] [Related]

  • 16. A machine learning approach to multi-level ECG signal quality classification.
    Li Q, Rajagopalan C, Clifford GD.
    Comput Methods Programs Biomed; 2014 Dec 05; 117(3):435-47. PubMed ID: 25306242
    [Abstract] [Full Text] [Related]

  • 17. Implementation and validation of real-time algorithms for atrial fibrillation detection on a wearable ECG device.
    Marsili IA, Biasiolli L, Masè M, Adami A, Andrighetti AO, Ravelli F, Nollo G.
    Comput Biol Med; 2020 Jan 05; 116():103540. PubMed ID: 31751811
    [Abstract] [Full Text] [Related]

  • 18. A 2.66 µW Clinician-Like Cardiac Arrhythmia Watchdog Based on P-QRS-T for Wearable Applications.
    Xu X, Cai Q, Zhao Y, Wang G, Zhao L, Lian Y.
    IEEE Trans Biomed Circuits Syst; 2022 Oct 05; 16(5):793-806. PubMed ID: 35900999
    [Abstract] [Full Text] [Related]

  • 19. A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm.
    Pandit D, Zhang L, Liu C, Chattopadhyay S, Aslam N, Lim CP.
    Comput Methods Programs Biomed; 2017 Jun 05; 144():61-75. PubMed ID: 28495007
    [Abstract] [Full Text] [Related]

  • 20. Detection of atrial fibrillation using discrete-state Markov models and Random Forests.
    Kalidas V, Tamil LS.
    Comput Biol Med; 2019 Oct 05; 113():103386. PubMed ID: 31446318
    [Abstract] [Full Text] [Related]

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