Fábio Mendonça


Biography
Fábio Mendonça received the BS and MSc degrees in electrical and telecommunications engineering from University of Madeira, and the PhD degree 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.
Publications
2023
Non-Destructive Banana Ripeness Detection Using Shallow and Deep Learning: A Systematic Review Journal Article
In: Sensors, vol. 23, no. 2, pp. 738, 2023.
2022
Heuristic Optimization of Deep and Shallow Classifiers: An Application for Electroencephalogram Cyclic Alternating Pattern Detection Journal Article
In: Entropy, vol. 24, no. 5, pp. 688, 2022.
Automatic detection of cyclic alternating pattern Journal Article
In: Neural Comput. Appl., vol. 34, no. 13, pp. 11097–11107, 2022.
ProBoost: a Boosting Method for Probabilistic Classifiers Journal Article
In: CoRR, vol. abs/2209.01611, 2022.
Variational Autoencoder Kernel Interpretation and Selection for Classification Journal Article
In: CoRR, vol. abs/2209.04715, 2022.
Heuristic Optimization of Deep and Shallow Classifiers: An Application for Electroencephalogram Cyclic Alternating Pattern Detection Journal Article
In: Entropy, vol. 24, no. 5, pp. 688, 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.
2019
A Review of Approaches for Sleep Quality Analysis Journal Article
In: IEEE Access, vol. 7, pp. 24527–24546, 2019.
A Portable Wireless Device for Cyclic Alternating Pattern Estimation from an EEG Monopolar Derivation Journal Article
In: Entropy, vol. 21, no. 12, pp. 1203, 2019.
A Systematic Review of Detecting Sleep Apnea Using Deep Learning Journal Article
In: Sensors, vol. 19, no. 22, pp. 4934, 2019.
A Review of Obstructive Sleep Apnea Detection Approaches Journal Article
In: IEEE J. Biomed. Health Informatics, vol. 23, no. 2, pp. 825–837, 2019.
2018
A portable wireless device based on oximetry for sleep apnea detection Journal Article
In: Computing, vol. 100, no. 11, pp. 1203–1219, 2018.
Sleep Quality Analysis with Cardiopulmonary Coupling Inproceedings
In: ICBEA, pp. 1–6, IEEE, 2018.
Automatic Detection of a Phases for CAP Classification Inproceedings
In: ICPRAM, pp. 394–400, SciTePress, 2018.
2017
A minimally invasive portable system for sleep apnea detection Conference
2017 International Conference and Workshop on Bioinspired Intelligence (IWOBI), 2017.
SpO2 based Sleep Apnea Detection using Deep Learning Conference
21st International Conference on Intelligent Engineering Systems (INES 2017), IEEE IEEE, Larnaca, Cyprus., 2017.
A minimallyinvasive portable system for sleep apnea detection Inproceedings
In: IWOBI, pp. 1–5, IEEE, 2017.
A Minimally Invasive Portable System for Sleep Apnea Detection Inproceedings
In: IWOBI, pp. 1–5, IEEE, 2017.