Mohd Zubir Suboh
Biographic Data
| ID | 10009650 |
|---|---|
| NAME | Mohd Zubir Suboh |
| GIVEN NAMES | Mohd Zubir |
| FAMILY NAME | Suboh |
| SIGNATURE | SUBOH M Z |
| AFFILIATIONS | University of Kuala Lumpur |
| ORCID | 0000-0001-8338-1010 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Analysis on Four Derivative Waveforms of Photoplethysmogram (PPG) for Fiducial Point Detection
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
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…
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Analysis on Four Derivative Waveforms of Photoplethysmogram (PPG) for Fiducial Point Detection
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
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)