| Biography | |
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 Dr. Raquel Sebastião University of Aveiro, Portugal |
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| Title: Learning from physiological signals | |
| Abstract: The autonomic nervous system ANS regulates fundamental physiological states which are typically involuntary, upregulating and downregulating various functions within our body. The ANS controls various organ systems inside the body, namely muscles, glands and organs within the body. While maintaining the equilibrium of the body’s systems according to both internal and external stimuli, many physiological signals reflect the activity of the ANS. As it functions without conscious control, ANS reactions, which is difficult to deceive. Biomedical sensors, which is usually minimally invasive equipment and with low compliance, are now often wireless and can continuously stream to devices that are commonplace in many households (like smartphones). Therefore, biomedical sensors offer an excellent opportunity to monitor the physiological correlates of several psychophysiological states of human subjects. Relevant information and meaningful characteristics from physiological signals can be obtained through the application of methods such as feature extraction methods or parameter free data mining (deep learning, clustering, classification or change detection). Recent studies have shown the importance of physiological signal processing techniques for the characterization and evaluation of several psychophysiological states, such as behavioral, stress, mood, emotional and affective, under several domain applications, in clinical and research scenarios. This talk will present examples of Autonomic Nervous System (ANS) correlates in psychophysiological states in different domain applications, such as: 1. Pollutants inhalation identification 2. Classification of mental disorders influences 3. Biometric Authentication 4. Pain assessment 5. Emotion characterization 6. Classification of mental disorders influences | |
| Biography: Raquel Sebastião is a researcher at Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro. She is PhD in Applied Mathematics, with a background in Applied Mathematics and Computational Methods, from University of Porto. She participated in several national and international R&D projects on multi-modality medical image registration, incremental and adaptive learning systems, modelling and control for personalized drug administration, image self-similarity, decision support in first responders’ scenarios. Her research activity has been in facial recognition, registration of multimodal images, data streams, synopsis structures, change detection approaches, decision support systems and biomedical applications. Currently, she is focused on data mining, information extraction and learning from physiological signals. She also has teaching experience, namely in mathematics, statistical and probabilistic methods, at the Polytechnic Institute of Viseu and at the University of Aveiro. | |
