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Mohd Zubir Suboh

Biographic Data

ID10009650
NAMEMohd Zubir Suboh
GIVEN NAMESMohd Zubir
FAMILY NAMESuboh
SIGNATURESUBOH M Z
AFFILIATIONSUniversity of Kuala Lumpur
ORCID0000-0001-8338-1010
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2022
H-INDEX0
  • Analysis on Four Derivative Waveforms of Photoplethysmogram (PPG) for Fiducial Point Detection

    Open Access•Mohd Zubir Suboh, Rosmina Jaafar et al.•ARTICLE•Frontiers in Public Health•2022

    Fiducial points of photoplethysmogram (PPG), first derivative PPG (VPG), and second derivative PPG (APG) are essential in extracting numerous parameters to diagnose cardiovascular disease. However, the fiducial points were usually detected using complex mathematical algorithms. Inflection points from derivatives waveforms are not thoroughly studied, whereas they can significantly assist in peak detection. This study is performed to investigate th…

  • Covid-19 Prediction With Machine Learning Technique From Extracted Features of Photoplethysmogram Morphology

    Open Access•Nazrul Anuar Nayan, Choon Jie Yi et al.•ARTICLE•Frontiers in Public Health•2022

    At present, COVID-19 is spreading widely around the world. It causes many health problems, namely, respiratory failure and acute respiratory distress syndrome. Wearable devices have gained popularity by allowing remote COVID-19 detection, contact tracing, and monitoring. In this study, the correlation of photoplethysmogram (PPG) morphology between patients with COVID-19 infection and healthy subjects was investigated. Then, machine learning was u…

No prominent works on this page.

  • Analysis on Four Derivative Waveforms of Photoplethysmogram (PPG) for Fiducial Point Detection

    Open Access•Mohd Zubir Suboh, Rosmina Jaafar et al.•ARTICLE•Frontiers in Public Health•2022

    Fiducial points of photoplethysmogram (PPG), first derivative PPG (VPG), and second derivative PPG (APG) are essential in extracting numerous parameters to diagnose cardiovascular disease. However, the fiducial points were usually detected using complex mathematical algorithms. Inflection points from derivatives waveforms are not thoroughly studied, whereas they can significantly assist in peak detection. This study is performed to investigate th…

  • Covid-19 Prediction With Machine Learning Technique From Extracted Features of Photoplethysmogram Morphology

    Open Access•Nazrul Anuar Nayan, Choon Jie Yi et al.•ARTICLE•Frontiers in Public Health•2022

    At present, COVID-19 is spreading widely around the world. It causes many health problems, namely, respiratory failure and acute respiratory distress syndrome. Wearable devices have gained popularity by allowing remote COVID-19 detection, contact tracing, and monitoring. In this study, the correlation of photoplethysmogram (PPG) morphology between patients with COVID-19 infection and healthy subjects was investigated. Then, machine learning was u…

Artificial Intelligence (2 works) · Computer Science (2 works) · Non-Invasive Vital Sign Monitoring (2 works) · Photoplethysmogram (2 works) · Cardiology (1 work) · Computer vision (1 work) · COVID-19 diagnosis using AI (1 work) · ECG Monitoring and Analysis (1 work) · Fiducial marker (1 work) · Heart Rate Variability and Autonomic Control (1 work)

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