Raquel Sebastião
Adjunct Professor
raquel [dot] sebastiao [at] ua [dot] pt
Member information
Status
Integrated Researcher
Research Group
Affiliation
Polytechnic Institute of Viseu
Ciência ID
Scopus
ORCID ID
Description
Raquel Sebastião holds a PhD in Applied Mathematics, with a background in Applied Mathematics and Computational Methods, from the University of Porto. She is an adjunct professor at the School of Technology and Management of Viseu, Polytechnic Institute of Viseu, and a researcher at the Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, with over 60 publications, with a total of more than 1000 citations, reaching an h-index of 14 (Scopus: Oct 2026). Her research in Informatics/Computer Science, particularly in the fields of Physiological Computing and Affective Computing, focuses on healthcare scenarios, with a particular emphasis on pain assessment. Regarding the understanding of pain mechanisms and objective, quantifiable measures to support self-care and promote patients’ health and well-being, she was awarded an assistant researcher contract by the FCT, project “Multimodal physiological indicators of pain” (DOI: 10.54499/CEECIND/03986/2018/CP1559/CT0028), to study the physiological responses of patients in postoperative pain, and with the project “Emotional Modulation in Pain Assessment” (2022.05005.PTDC), in which she was the principal investigator. She has participated in several national and international R&D projects, is a member of the program committee of several conferences, serves as a reviewer of several journals, and has been enrolled in the organization of scientific events. She has supervised several students (undergraduate, Masters, and PhDs), has been jury for academic degrees and several undergraduate courses. Keywords: data mining, decision support, artificial Intelligence, machine learning, adaptive systems, computer-related health issues, and patient-centred medicine.
Projects
Publications
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2026
Demographic-Agnostic ECG Biometrics: Addressing Bias in Deep Learning-Based Personal Identification Communications in Computer and Information Science, 2839 CCIS, 522–537
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2026
ECG-Based Biometric Identification: An Exploratory Study Using Fingertip Signals Acquired with Solid-State Electrodes Lecture Notes in Computer Science, 15937 LNCS, 187–198
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2026
Encoding clinical preferences via resampling: an application to pain assessment Pattern Analysis and Applications, 29(3), 117
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2026
Informed Decision Making Strategy for Resampling in Pain Assessment Lecture Notes in Computer Science, 15938 LNCS, 147–158
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2026
Respiratory Signal Processing and Analysis Using Flexible Capacitive Sensor Data Advanced Materials Technologies, 11(10), e02118
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2025
A Review on Intelligent Systems for ECG Analysis: From Flexible Sensing Technology to Machine Learning IEEE Journal of Biomedical and Health Informatics, 29(5), 3398–3413
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2025
Change Detection in Electrocardiogram (ECG) Signals After Postoperative Pain Management Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
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2025
Decoding pain: prediction under different emotional contexts through physiological signals International Journal of Data Science and Analytics, 19(3), 585–602
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2025
Emotion-Enhanced Pain Assessment Protocol Lecture Notes in Computer Science, 15504 LNCS, 385–400
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2025
Explaining Pain: On the Impact of Physiological Signals in Pain Prediction Lecture Notes in Computer Science, 15556 LNCS, 70–87
