Towards Emotionally Intelligent Virtual Environments: Classifying Emotions through a Biosignal-Based Approach

Ebubekir Enes Arslan, Mehmet Feyzi Akşahin, Murat Yilmaz, Hüseyin Emre Ilgın

Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

5 Lataukset (Pure)

Abstrakti

This paper introduces a novel method for emotion classification within virtual reality (VR) environments, which integrates biosignal processing with advanced machine learning techniques. It focuses on the processing and analysis of electrocardiography (ECG) and galvanic skin response (GSR) signals, which are established indicators of emotional states. To develop a predictive model for emotion classification, we extracted key features, i.e., heart rate variability (HRV), morphological characteristics, and Hjorth parameters. We refined the dataset using a feature selection process based on statistical techniques to optimize it for machine learning applications. The model achieved an accuracy of 97.78% in classifying emotional states, demonstrating that by accurately identifying and responding to user emotions in real time, VR systems can become more immersive, personalized, and emotionally resonant. Ultimately, the potential applications of this method are extensive, spanning various fields. Emotion recognition in education would allow further implementation of adapted learning environments through responding to the current emotional states of students, thereby fostering improved engagement and learning outcomes. The capability for emotion recognition could be used by virtual systems in psychotherapy to provide more personalized and effective therapy through dynamic adjustments of the therapeutic content. Similarly, in the entertainment domain, this approach could be extended to provide the user with a choice regarding emotional preferences for experiences. These applications highlight the revolutionary potential of emotion recognition technology in improving the human-centric nature of digital experiences.
AlkuperäiskieliEnglanti
Artikkeli8769
JulkaisuApplied Sciences
Vuosikerta14
Numero19
DOI - pysyväislinkit
TilaJulkaistu - lokak. 2024
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 1

Sormenjälki

Sukella tutkimusaiheisiin 'Towards Emotionally Intelligent Virtual Environments: Classifying Emotions through a Biosignal-Based Approach'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Siteeraa tätä