Mojisola Grace Asogbon


NameMojisola Grace Asogbon
Job titleEarly Career Academic - Data Science
Research instituteCollege of Science and Engineering

Research outputs

Investigation of Artifact Contamination Impact on EEG Oscillations Towards Enhanced Motor Function Characterization

Asogbon, M.G., Samuel, O., Meziane, F., Li, G. and Li, Y. 2024. Investigation of Artifact Contamination Impact on EEG Oscillations Towards Enhanced Motor Function Characterization. 17th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSIGNALS. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0012373400003657

A Multi-Dataset Characterization of Window-based Hyperparameters for Deep CNN-driven sEMG Pattern Recognition

Kulwa, F., Zhang, H., Samuel, O., Asogbon, M., Scheme, E., Kushaba, R., McEwan, A. and Li, G. 2023. A Multi-Dataset Characterization of Window-based Hyperparameters for Deep CNN-driven sEMG Pattern Recognition. IEEE Transactions on Human-Machine Systems. pp. 1-12. https://doi.org/10.1109/THMS.2023.3329536

Analysis of Artifactual Components Rejection Threshold towards Enhanced Characterization of Neural Activity in Post-Stroke Survivor

Asogbon, M., Huai, Y., Samuel, O., Jing, Z., Ma, Y., Liu, J., Jiang, Y., Fu, Y., Li, G. and Li, Y. 2023. Analysis of Artifactual Components Rejection Threshold towards Enhanced Characterization of Neural Activity in Post-Stroke Survivor. 45th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society. IEEE Xplore. https://doi.org/https://doi.org/10.1109/EMBC40787.2023.10340688

Enhanced Deep Transfer Learning Model based on Spatial-Temporal driven Scalograms for Precise Decoding of Motor Intent in Stroke Survivors

Samuel, O., Asogbon, M., Kulwa, F., Zangene, A., Oyemakinde, T., Igbe, T., McEwan, A., Li, Y. and Li, G. 2023. Enhanced Deep Transfer Learning Model based on Spatial-Temporal driven Scalograms for Precise Decoding of Motor Intent in Stroke Survivors. 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE. https://doi.org/10.1109/EMBC40787.2023.10340683

A Novel Duo-Stage driven Deep Neural Network Approach for Mitigating Electrode Shift Impact on Myoelectric Pattern Recognition Systems

Kulwa, F., Samuel, O.W., Asogbon, M., Oyemakinde, T.T., Obe, O.O. and Li, G. 2023. A Novel Duo-Stage driven Deep Neural Network Approach for Mitigating Electrode Shift Impact on Myoelectric Pattern Recognition Systems. 2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE. https://doi.org/10.1109/MeMeA57477.2023.10171910
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