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Publications

Publications by João Gama

2025

Interpretable Rules for Online Failure Prediction: A Case Study on the Metro do Porto dataset

Authors
Jakobs, M; Veloso, B; Gama, J;

Publication
CoRR

Abstract

2024

Emotion-Enhanced Pain Assessment Protocol

Authors
Alves, B; Almeida, A; Silva, C; Pais, D; Ribeiro, RP; Gama, J; Fernandes, JM; Brás, S; Sebastião, R;

Publication
Human and Artificial Rationalities. Advances in Cognition, Computation, and Consciousness - Third International Conference, HAR 2024, Paris, France, September 17-20, 2024, Proceedings

Abstract
Pain is a highly subjective phenomenon that depends on multiple factors. The common methods used to evaluate pain require the person to be awakened and cooperative, which may not always be possible. Moreover, such methods are subject to non-quantifiable influences, namely the impact of an individual’s emotional state on how pain is perceived or how negative emotions may exacerbate pain perception, while positive emotions may attenuate it. The goal of this study was to conduct a novel protocol for pain induction with emotional elicitation and assess its feasibility. In this protocol, the physiological responses were monitored, and collected, through Electrocardiogram, Electrodermal Activity, and surface Electromyogram signals. Along the protocol, the pain perception was evaluated using a 0–10 numerical rating scale and by registering the time from the pain stimulus beginning to the Pain and Tolerance Thresholds. This study comprised three emotional sessions, negative, positive, and neutral, which were performed through videos of excerpts of terror, comedy, and documentary films, respectively, followed by pain induction using the Cold Pressor Task (CPT). A total of 56 participants performed the study, with a CPT mean time of about 91.70 ± 39.64 s among all the sessions. The conducted protocol was considered feasible and safe as it allowed the collection of physiological data, pain, and questionnaires’ reports from 56 participants, without any harm to them. Moreover, the collected data can be further used to assess how emotional conditions influence pain perception and to provide better emotion-calibrated pain recognition systems based on physiological signals. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

2025

A Deep Learning Framework for Medium-Term Covariance Forecasting in Multi-Asset Portfolios

Authors
Reis, P; Serra, AP; Gama, J;

Publication
CoRR

Abstract

2025

On-device edge learning for IoT data streams: a survey

Authors
Lourenço, A; Rodrigo, J; Gama, J; Marreiros, G;

Publication
CoRR

Abstract

2025

In-context learning of evolving data streams with tabular foundational models

Authors
Lourenço, A; Gama, J; Xing, EP; Marreiros, G;

Publication
CoRR

Abstract

2025

DFDT: Dynamic Fast Decision Tree for IoT Data Stream Mining on Edge Devices

Authors
Lourenço, A; Rodrigo, J; Gama, J; Marreiros, G;

Publication
CoRR

Abstract

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