Publications by authors named "Sunday Olusanya Olatunji"
Purpose: The first novel coronavirus disease-19 (COVID-19) case in the Kingdom of Saudi Arabia (KSA) was reported in Qatif in March 2020 with continual increase in infection and mortality rates since then. In this study, we aim to determine risk factors which effect severity and mortality rates in a cohort of hospitalized COVID-19 patients in KSA.
Method: We reviewed medical records of hospitalized patients with confirmed COVID-19 positive results via reverse-transcriptase-polymerase-chain-reaction (RT-PCR) tests at Prince Mohammed Bin Abdulaziz Hospital, Riyadh between May and August 2020.
Article Synopsis
- Researchers used support vector regression (SVR) modeling to estimate knee torque from mechanomyographic (MMG) signals in individuals with spinal cord injuries during NMES-assisted knee extension.
- The SVR model achieved high estimation accuracy, with R-values of 95% for training and 94% for testing with a Gaussian kernel and slightly lower values for a polynomial kernel.
- The findings suggest that MMG signals can effectively serve as a proxy for NMES-assisted torque, paving the way for improved applications in research and clinical practices involving NMES systems.
Background And Objectives: The refractive index of hemoglobin plays important role in hematology due to its strong correlation with the pathophysiology of different diseases. Measurement of the real part of the refractive index remains a challenge due to strong absorption of the hemoglobin especially at relevant high physiological concentrations. So far, only a few studies on direct measurement of refractive index have been reported and there are no firm agreements on the reported values of refractive index of hemoglobin due to measurement artifacts.
View Article and Find Full Text PDFThe difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG) of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR) due to its good generalization ability in related fields.
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