Ku Nurul Fazira Ku Azir
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Ku Nurul Fazira Ku Azir
Official Name
Ku Azir, Ku Nurul Fazira
Alternative Name
Ku Azir, Ku Nurul Fazira
Fazira Ku Azir, Ku Nurul
Azir, Ku
Azir, Ku Nurul Fazira Ku
Azir, K. N.F.K.
Ku Azir, K. N.F.
Azir, K. N.F.Ku
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Scopus Author ID
56879016500
Researcher ID
AAY-3466-2021

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  • Publication
    A general framework for improving electrocardiography monitoring system with machine learning
    ( 2019-03-01)
    Khairuddin A.M.
    ;
    Ku Nurul Fazira Ku Azir
    ;
    Eh Kan P.
    As one of the most important health monitoring systems, electrocardiography (ECG) is used to obtain information about the structure and functions of the human heart for detecting and preventing cardiovascular disease. Given its important role, it is vital that the ECG monitoring system provides relevant and accurate information about the heart. Over the years, numerous attempts were made to design and develop more effective ECG monitoring system. Nonetheless, the literature reveals not only several limitations in conventional ECG monitoring system but also emphasizes on the need to adopt new technology such as machine learning to improve the monitoring system as well as its medical applications. This paper reviews previous works on machine learning to explain its key features, capabilities as well as presents a general framework for improving ECG monitoring system.