Year 2022

• Emotion Recognition from Physiological Channels Using Graph Neural Network

  Publication

  • T. Wierciński
  • M. Rock
  • R. Zwierzycki
  • T. Zawadzka
  • M. Zawadzki

  - SENSORS - Year 2022

  In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...

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Year 2021

• Graph Representation Integrating Signals for Emotion Recognition and Analysis

  Publication

  • T. Zawadzka
  • T. Wierciński
  • G. Meller
  • M. Rock
  • R. Zwierzycki
  • M. Wróbel

  - SENSORS - Year 2021

  Data reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...

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