Real-Life Validation of Emotion Detection System with Wearables

• Autores: Dominika Kunc, Joanna Komoszyńska, Bartosz Perz, Przemysław Kazienko, Stanisław Saganowski
• Localización: Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence: 9th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, May 31 – June 3, 2022, Proceedings, Part II / José Manuel Ferrández Vicente (dir. congr.), José Ramón Álvarez Sánchez (dir. congr.), Félix de la Paz López (dir. congr.), Hojjat Adeli (aut.), 2022, ISBN 978-3-031-06527-9, págs. 45-54
• Idioma: inglés
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• Resumen

  • Emotion recognition in real life is challenging since training machine learning models requires many annotated samples with experienced emotions. Although collecting such data is a difficult task, we may improve the process by utilizing a pre-trained model detecting emotional events. We conducted a study to test whether employing machine learning models that detect intense emotions to trigger self-assessments collects more data than triggering self-reports randomly. We have examined the performance of three models on 13 participants for three months. Results show that our models enhance the data collection and provide on average 21% more emotionally annotated data in the general setup. The personalized model improves the collection even more – by up to 38%.