Fábio Mendonça
Biography
Fábio Mendonça received the BS and MSc degrees in electrical and telecommunications engineering from the University of Madeira and the PhD in electrical and computer engineering from Instituto Superior Técnico – University of Lisbon in partnership with Carnegie Mellon University. He works at the University of Madeira and is a researcher with the Interactive Technologies Institute – LARSyS. His research interests include sleep analysis, pattern recognition, and machine learning.
Related Projects
Publications
2022
Multiple Time Series Fusion Based on LSTM: An Application to CAP A Phase Classification Using EEG Journal Article
In: International Journal of Environmental Research and Public Health, vol. 19, no. 17, pp. 688, 2022.
2021
A method based on cardiopulmonary coupling analysis for sleep quality assessment with FPGA implementation Journal Article
In: Artif. Intell. Medicine, vol. 112, pp. 102019, 2021.
Multiple Time Series Fusion Based on LSTM An Application to CAP A Phase Classification Using EEG Journal Article
In: CoRR, vol. abs/2112.11218, 2021.
Multiple Time Series Fusion Based on LSTM An Application to CAP A Phase Classification Using EEG Journal Article
In: arXiv, 2021.
2020
Multi-Objective Hyperparameter Optimization of Convolutional Neural Network for Obstructive Sleep Apnea Detection Journal Article
In: IEEE Access, vol. 8, pp. 129586–129599, 2020.
A Method for Sleep Quality Analysis Based on CNN Ensemble With Implementation in a Portable Wireless Device Journal Article
In: IEEE Access, vol. 8, pp. 158523–158537, 2020.
Cyclic alternating pattern estimation based on a probabilistic model over an EEG signal Journal Article
In: Biomed. Signal Process. Control., vol. 62, pp. 102063, 2020.
Matrix of Lags: A tool for analysis of multiple dependent time series applied for CAP scoring Journal Article
In: Comput. Methods Programs Biomed., vol. 189, pp. 105314, 2020.
SC3: self-configuring classifier combination for obstructive sleep apnea Journal Article
In: Neural Comput. Appl., vol. 32, no. 24, pp. 17825–17841, 2020.
An Oximetry Based Wireless Device for Sleep Apnea Detection Journal Article
In: Sensors, vol. 20, no. 3, pp. 888, 2020.