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Acquisition and Synchronisation of Multi-source Physiological Data Using Microservices and Event-Driven Architecture., , , and . ISAmI, volume 603 of Lecture Notes in Networks and Systems, page 13-23. Springer, (2022)One-dimensional convolutional neural networks for low/high arousal classification from electrodermal activity., , , and . Biomed. Signal Process. Control., 71 (Part): 103203 (2022)Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review., , , , and . Sensors, 22 (22): 8886 (2022)Defect detection and classification on semiconductor wafers using two-stage geometric transformation-based data augmentation and SqueezeNet lightweight convolutional neural network., , , , and . Comput. Ind. Eng., (September 2023)Detection of auditory hallucinations from electroencephalographic brain-computer interface signals., , , , , , and . Cogn. Syst. Res., (January 2024)Generic Architecture for Multisource Physiological Signal Acquisition, Processing and Classification Based on Microservices., , , , , and . DCAI (1), volume 740 of Lecture Notes in Networks and Systems, page 123-133. Springer, (2023)A deep residual neural network for semiconductor defect classification in imbalanced scanning electron microscope datasets., , , , and . Appl. Soft Comput., (2022)Emotion Classification from EEG with a Low-Cost BCI Versus a High-End Equipment., , , , , , and . Int. J. Neural Syst., 32 (10): 2250041:1-2250041:19 (2022)Electroencephalographic Signal Processing from Brain-Computer-Interface Following Image-Based Emotion Induction., , , , , and . ISAmI, volume 603 of Lecture Notes in Networks and Systems, page 239-248. Springer, (2022)Distributed Architecture for Acquisition and Processing of Physiological Signals., , , , and . UCAmI, volume 31 of MDPI Proceedings, page 30. MDPI, (2019)