Dr Javier Andreu-Perez

Filippetti, ML., Andreu-Perez, J., Klerk, CD., Richmond, C. and Rigato, S., (2022). Are advanced methods necessary to improve infant fNIRS data analysis? An assessment of baseline-corrected averaging, general linear model (GLM) and multivariate pattern analysis (MVPA) based approaches

Jamalifard, M., Andreu-Perez, J., Hagras, H. and Martinez, L., (2024). Fuzzy Norm-Explicit Product Quantization for Recommender Systems. IEEE Transactions on Fuzzy Systems, 1-12

Ramos-Cruz, B., Andreu-Perez, J. and Martínez, L., (2024). The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research. Neurocomputing. 581, 127427-127427

Fumanal-Idocin, J., Vidaurre, C., Fernández, J., Gómez, M., Andreu-Perez, J., Prashad, M. and Bustince, H., (2024). Supervised Penalty-based Aggregation Applied to Motor-Imagery based Brain-Computer-Interface. Pattern Recognition. 145, 109924-109924

Filippetti, ML., Andreu-Perez, J., De Klerk, C. and Rigato, S., (2023). Are advanced methods necessary to improve infant fNIRS data analysis? An assessment of baseline-corrected averaging, general linear model (GLM) and multivariate pattern analysis (MVPA) based approaches. NeuroImage. 265, 119756-119756

Kiani, M., Andreu-Perez, J. and Hagras, H., (2023). A Temporal Type-2 Fuzzy System for Time-dependent Explainable Artificial Intelligence. IEEE Transactions on Artificial Intelligence. 4 (3), 573-586

Tanveer, M., Lin, C-T., Ting, C-K. and Andreu-Perez, J., (2023). Guest Editorial: Special Issue on Emerging Computational Intelligence Techniques to Address Challenges in Biomedical Data and Imaging. IEEE Transactions on Emerging Topics in Computational Intelligence. 7 (2), 292-294

Soheil, S., Andreu-Perez, J., Akoth, C., Bosch-Capblanch, X., Dasgupta, S., Falchetta, G., Gregson, S., Hammad, AT., Herringer, M., Kapkea, F., Labella, A., Lisciotto, L., Martínez, L., Macharia, PM., Morales-Ruiz, P., Murage, N., Offeddu, V., South, A., Torbica, A., Trentini, F. and Alessia, M., (2023). Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework. PLoS One. 18 (8), e0275037-e0275037

Chaudhary, L., Girdhar, N., Sharma, D., Andreu-Perez, J., Doucet, A. and Renz, M., (2023). A Review of Deep Learning Models for Twitter Sentiment Analysis: Challenges and Opportunities. IEEE Transactions on Computational Social Systems, 1-30

Kiani, M., Andreu-Perez, J., Hagras, H., Papageorgiou, EI., Prasad, M. and Lin, C-T., (2022). Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics. IEEE Transactions on Cognitive and Developmental Systems. 14 (1), 50-63

Ranjbar, E., Menhaj, MB., Suratgar, AA., Andreu-Perez, J. and Prasad, M., (2022). Modern control design for MEMS tunable capacitors in voltage reference applications: a comparative study. International Journal of Dynamics and Control. 10 (2), 483-510

Ding, W., Feng, Z., Andreu-Perez, J. and Pedrycz, W., (2022). Derived Multi-population Genetic Algorithm for Adaptive Fuzzy C-Means Clustering. Neural Processing Letters. 55 (3), 2023-2047

Gupta, PK. and Andreu-Perez, J., (2022). Enhanced Type-2 Wang-Mendel Approach. Journal of Experimental and Theoretical Artificial Intelligence, 1-26

Gupta, A., Kumar, D., Verma, H., Tanveer, M., Andreu-Perez, J., Lin, C-T. and Prasad, M., (2022). Recognition of multi-cognitive tasks from EEG signals using EMD methods. Neural Computing and Applications. 35 (31), 22989-23006

Andreu-Perez, J., Perez-Espinosa, H., Timonet, E., Kiani, M., Giron-Perez, MI., Benitez-Trinidad, AB., Jarchi, D., Rosales, A., Gkatzoulis, N., Reyes-Galaviz, OF., Torres, A., Alberto Reyes-Garcia, C., Ali, Z. and Rivas, F., (2022). A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels. IEEE Transactions on Services Computing. 15 (3), 1220-1232

K. Gupta, P. and Andreu-Perez, J., (2022). A Gentle Introduction and Survey on Computing with Words (CWW) Methodologies. Neurocomputing. 500, 921-937

Salami, A., Andreu-Perez, J. and Gillmeister, H., (2022). EEG-ITNet: An Explainable Inception Temporal Convolutional Network for Motor Imagery Classification. IEEE Access. 10, 36672-36685

Vega, CF., Quevedo, J., Escandón, E., Kiani, M., Ding, W. and Andreu-Perez, J., (2022). Fuzzy Temporal Convolutional Neural Networks in P300-based Brain-Computer Interface for Smart Home Interaction. Applied Soft Computing. 117, 108359-108359

Andreu-Perez, J., Hagras, H., Kiani, M., Rigato, S. and Filippetti, ML., (2022). Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives. IEEE Computational Intelligence Magazine. 17 (1), 16-33

Gupta, A., Agrawal, RK., Kirar, JS., Andreu-Perez, J., Ding, W-P., Lin, C-T. and Prasad, M., (2021). On the Utility of Power Spectral Techniques With Feature Selection Techniques for Effective Mental Task Classification in Noninvasive BCI. IEEE Transactions on Systems Man and Cybernetics: Systems. 51 (5), 3080-3092

Andreu-Perez, J. and Kiani, M., (2021). Single-Trial Recognition of Video Gamer’s Expertise from Brain Haemodynamic and Facial Emotion Responses. Brain Sciences. 11 (1), 106-106

Ranjbar, E., Menhaj, MB., Suratgar, AA., Andreu-Perez, J. and Prasad, M., (2021). Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source. SN Applied Sciences. 3 (6)

Gupta, PK., Sharma, D. and Andreu-Perez, J., (2021). Enhanced Linguistic Computational Models and Their similarity with Yager’s Computing with Words. Information Sciences. 574, 259-278

Andreu-Perez, J., Emberson, LL., Kiani, M., Filippetti, ML., Hagras, H. and Rigato, S., (2021). Explainable Artificial Intelligence Based Analysis for Developmental Cognitive Neuroscience. Communications Biology. 4 (1), 1077-

Perez-Espinosa, H., Timonet-Andreu, E. and Andreu-Perez, J., (2021). Bias and privacy in AI's cough-based COVID-19 recognition. The Lancet Digital Health. 3 (12), e760-e760

Chowdhury, A. and Andreu-Perez, J., (2021). Clinical Brain-Computer Interface Challenge 2020 (CBCIC at WCCI2020): Overview, methods and results. IEEE Transactions on Medical Robotics and Bionics. 3 (3), 661-670

Akshansh, G., R. K., A., Jyoti Singh, K., Baljeet, K., Weiping, D., Chin-Teng, L., Andreu-Perez, J. and Mukesh, P., (2020). A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces. Neurocomputing. 389, 207-217

Andreu-Perez, J., (2020). Fuzzy learning and its applications in neural-engineering. Neurocomputing. 389, 196-197

Jarchi, D., Andreu-Perez, J., Kiani, M., Vysata, O., Kuchynka, J., Prochazka, A. and Sanei, S., (2020). Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning. Sensors. 20 (9), 2594-2594

Salami, A., Andreu-Perez, J. and Gillmeister, H., (2020). Symptoms of depersonalisation/derealisation disorder as measured by brain electrical activity: A systematic review. Neuroscience and Biobehavioral Reviews. 118, 524-537

Andreu-Perez, J., Cao, F., Hagras, H. and Yang, G., (2018). A Self-Adaptive Online Brain Machine Interface of a Humanoid Robot through a General Type-2 Fuzzy Inference System. IEEE Transactions on Fuzzy Systems. 26 (1), 101-116

Andreu-Perez, J., Deligianni, F., Ravì, D. and Yang, G-Z., (2018). Artificial Intelligence and Robotics.. CoRR. abs/1803.10813

Ravi, D., Wong, C., Deligianni, F., Berthelot, M., Andreu-Perez, J., Lo, B. and Yang, G-Z., (2017). Deep Learning for Health Informatics. IEEE Journal of Biomedical and Health Informatics. 21 (1), 4-21

Andreu-Perez, J., Garcia-Gancedo, L., McKinnell, J., Van der Drift, A., Powell, A., Hamy, V., Keller, T. and Yang, G-Z., (2017). Developing Fine-Grained Actigraphies for Rheumatoid Arthritis Patients from a Single Accelerometer Using Machine Learning. Sensors. 17 (9), 2113-2113

Andreu-Perez, J., Leff, DR., Shetty, K., Darzi, A. and Yang, G-Z., (2016). Disparity in Frontal Lobe Connectivity on a Complex Bimanual Motor Task Aids in Classification of Operator Skill Level. Brain Connectivity. 6 (5), 375-388

Andreu-Perez, J., Solnais, C. and Sriskandarajah, K., (2016). EALab (Eye Activity Lab): a MATLAB Toolbox for Variable Extraction, Multivariate Analysis and Classification of Eye-Movement Data. Neuroinformatics. 14 (1), 51-67

Andreu-Perez, J., Leff, DR., Ip, HMD. and Yang, G-Z., (2015). From Wearable Sensors to Smart Implants-–Toward Pervasive and Personalized Healthcare. IEEE Transactions on Biomedical Engineering. 62 (12), 2750-2762

Andreu-Perez, J., Poon, CCY., Merrifield, RD., Wong, STC. and Yang, G-Z., (2015). Big Data for Health. IEEE Journal of Biomedical and Health Informatics. 19 (4), 1193-1208

Solnais, C., Andreu-Perez, J., Sánchez-Fernández, J. and Andréu-Abela, J., (2013). The contribution of neuroscience to consumer research: A conceptual framework and empirical review. Journal of Economic Psychology. 36, 68-81

Andreu, J. and Angelov, P., (2013). An evolving machine learning method for human activity recognition systems. Journal of Ambient Intelligence and Humanized Computing. 4 (2), 195-206

Sadeghi-Tehran, P., Andreu, J., Angelov, P. and Zhou, X., (2011). Intelligent leader-follower behaviour for unmanned ground-based vehicles. Journal of Automation Mobile Robotics and Intelligent Systems. 5, 36-46

Andréu, J. and Holgado, JA., (2004). Wireless Sensor Networks applied to Ambient Assisted-Living Environments

Córdova, JC., Vega, CF. and Andreu-Perez, J., (2023). EMGTFNet: Fuzzy Vision Transformer to Decode Upperlimb sEMG Signals for Hand Gestures Recognition.

Córdova, JC., Flores, C. and Andreu-Perez, J., (2023). EMGTFNet: Fuzzy Vision Transformer to Decode Upperlimb sEMG Signals for Hand Gestures Recognition

Miranda, JA., Montoro, AP., Lopez-Ongil, C. and Andreu-Perez, J., (2022). Towards Interval Type-2 Fuzzy-Based PPG Quality Assessment for Physiological Monitoring

Reddy, TK., Wang, Y-K., Lin, C-T. and Andreu-Perez, J., (2021). JOINT APPROXIMATE DIAGONALIZATION DIVERGENCE BASED SCHEME FOR EEG DROWSINESS DETECTION BRAIN COMPUTER INTERFACES

Sharma, D., Gupta, PK., Andreu-Perez, J., Mendel, JM. and Lopez, LM., (2021). A Python Software Library for Computing with Words and Perceptions

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Fitz, S., (2021). A Type-2 Fuzzy Logic Based Explainable AI Approach for the Easy Calibration of AI models in IoT Environments

del Angel Arrieta, F., Rojas Cisneros, M., Rivas, JJ., Castrejon, LR., Sucar, LE., Andreu-Perez, J. and Orihuela-Espina, F., (2021). Characterization of a Raspberry Pi as the Core for a Low-cost Multimodal EEG-fNIRS Platform

Cortez, S., Flores, C. and Andreu-Perez, J., (2020). Improving Speller BCI performance using a cluster-based under-sampling method

Salami, A., Andreu-Perez, J. and Gillmeister, H., (2020). Towards Decoding of Depersonalisation Disorder Using EEG: A Time Series Analysis Using CDTW

Malik, A., de Frein, R., Al-Zeyadi, M. and Andreu-Perez, J., (2020). Intelligent SDN Traffic Classification Using Deep Learning: Deep-SDN

Cortez, SA., Flores Vega, C. and Andreu-Perez, J., (2020). Under-sampling and Classification of P300 Single-Trials using Self-Organized Maps and Deep Neural Networks for a Speller BCI

Cortez, SA., Flores, C. and Andreu-Perez, J., (2020). Single-trial P300 classification using deep belief networks for a BCI system

Kiani, M., Andreu-Perez, J., Hagras, H., Filippetti, ML. and Rigato, S., (2020). A Type-2 Fuzzy Logic Based Explainable Artificial Intelligence System for Developmental Neuroscience

Al-Zeyadi, M., Andreu-Perez, J., Hagras, H., Royce, C., Smith, D., Rzonsowski, P. and Malik, A., (2020). Deep Learning Towards Intelligent Vehicle Fault Diagnosis

Rozman, J., Hagras, H., Andreu-Perez, J., Clarke, D., Muller, B. and Data, SF., (2020). Privacy-Preserving Gesture Recognition with Explainable Type-2 Fuzzy Logic Based Systems

Cortez, SA., Flores, C. and Andreu-Perez, J., (2020). A Smart Home Control Prototype Using a P300-Based Brain–Computer Interface for Post-stroke Patients

Kiani, M., Andreu-Perez, J., Hagras, H., Andreu, AR., Pinto, M., Andreu, J., Reddy, P. and Izzetoglu, K., (2019). Towards Gamers’ Experience Level Decoding with Optical Brain Imaging

Achanccaray, D., Mylonas, G. and Andreu-Perez, J., (2019). An Implicit Brain Computer Interface Supported by Gaze Monitoring for Virtual Therapy

Achanccaray, D., Flores, C., Fonseca, C. and Andreu-Perez, J., (2018). A Fuzzy Genetic Algorithm for Optimal Spatial Filter Selection for P300-Based Brain Computer Interfaces

Flores, C., Fonseca, C., Achanccaray, D. and Andreu-Perez, J., (2018). Performance Evaluation of a P300 Brain-Computer Interface Using a Kernel Extreme Learning Machine Classifier

Flores, C., Flores, V., Achanccaray, D. and Andreu-Perez, J., (2018). A Convolutional Neural Network Approach for a P300-based Brain-Computer Interface for Disabled and Healthy Subjects

Achanccaray, D., Flores, C., Fonseca, C. and Andreu-Perez, J., (2017). A P300-based brain computer interface for smart home interaction through an ANFIS ensemble

Kiani, M., Andreu-Perez, J. and Papageorgiou, EI., (2017). Improved estimation of effective brain connectivity in functional neuroimaging through higher order fuzzy cognitive maps

Achanccaray, D., Acuna, K., Carranza, E. and Andreu-Perez, J., (2017). A virtual reality and brain computer interface system for upper limb rehabilitation of post stroke patients

Pacheco, K., Acuna, K., Carranza, E., Achanccaray, D. and Andreu-Perez, J., (2017). Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation

Kiani, M., Andreu-Perez, J., Leff, DR., Darzi, A. and Yang, GZ., (2014). Shedding Light on Surgeons' Cognitive Resilience: A Novel Method of Topological Analysis for Brain Networks

Angelov, P., Andreu, J. and Vuong, T., (2012). Automatic mobile photographer and picture diary

Sadeghi-Tehran, P., Behera, S., Angelov, P. and Andreu, J., (2012). Autonomous visual self-localization in completely unknown environment

Andreu, J., Baruah, RD. and Angelov, P., (2011). Real time recognition of human activities from wearable sensors by evolving classifiers

Andreu, J., Baruah, RD. and Angelov, P., (2011). Automatic scene recognition for low-resource devices using evolving classifiers

Baruah, RD., Angelov, P. and Andreu, J., (2011). Simpl_eClass: simplified potential-free evolving fuzzy rule-based classifiers

Baruah, RD., Angelov, P., Andreu, J. and IEEE, (2011). Simpl_eClass: Simplified Potential-free Evolving Fuzzy Rule-Based Classifiers

Andreu, J. and Angelov, P., (2010). Real-time human activity recognition from wireless sensors using evolving fuzzy systems

Andreu, J. and Angelov, P., (2010). Forecasting time-series for NN GC1 using Evolving Takagi-Sugeno (eTS) Fuzzy Systems with on-line inputs selection

Andréu, J., Viúdez, J. and Holgado, JA., (2009). An ambient assisted-living architecture based on wireless sensor networks

Pérez, JA., Álvarez, JA., Fernández-Montes, A. and Ortega, JA., (2009). Service-oriented device integration for ubiquitous ambient assisted living environments

Andréu, J., Viudez, J. and Holgado, J., (2008). A Survey of Wireless Sensor Networks

Viúdez, J., Andréu, J. and Holgado, JA., (2008). An OSGi Experience for Home Automation Applications