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    Hyperuricemia Prediction Using Photoplethysmogram and Arteriograph

    Hafifah Ab Hamid1, Nazrul Anuar Nayan1,*, Mohd Zubir Suboh1, Nurin Izzati Mohamad Azizul1, Mohamad Nazhan Mohd Nizar1, Amilia Aminuddin2, Mohd Shahrir Mohamed Said3, Saharuddin Ahmad4

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 287-304, 2022, DOI:10.32604/cmc.2022.021987

    Abstract Hyperuricemia is an alarming issue that contributes to cardiovascular disease. Uric acid (UA) level was proven to be related to pulse wave velocity, a marker of arterial stiffness. A hyperuricemia prediction method utilizing photoplethysmogram (PPG) and arteriograph by using machine learning (ML) is proposed. From the literature search, there is no available papers found that relates PPG with UA level even though PPG is highly associated with vessel condition. The five phases in this research are data collection, signal preprocessing including denoising and signal quality indexes, features extraction for PPG and SDPPG waveform, statistical analysis for feature selection and classification… More >

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