Details

Autor(en) / Beteiligte

• Ahmad, Akram
• Singh, Vaishali
• Upreti, Kamal
• Hameed, Alaa Ali
• García Márquez, Fausto Pedro
• Eken, Süleyman
• Jamil, Akhtar
• Ramirez, Isaac Segovia

Titel

A Systematic Study on Unimodal and Multimodal Human Computer Interface for Emotion Recognition

Ist Teil von

• Computing, Internet of Things and Data Analytics, 2024, Vol.1145, p.363-375

Ort / Verlag

Switzerland: Springer International Publishing AG

Erscheinungsjahr

2024

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• A systematic study for human-computer interface (HCI) for emotion recognition is presented in this paper, with a focus on various methods used to identify and interpret human emotions. It delves into various methods used to identify and interpret human emotions and highlights the limitations of unimodal HCI for emotion recognition systems. The paper emphasizes the benefits of multimodal HCI and how combining different types of data can lead to more accurate results. Additionally, it highlights the importance of using multiple modalities for emotion recognition. The study has significant implications for mental health assessments and interventions as it offers insights into the latest techniques and advancements in emotion recognition. Future research can use these insights to improve the accuracy of emotion recognition systems, ultimately leading to better mental health assessments and interventions. Overall, the paper provides a valuable contribution to the field of HCI and emotion recognition, and it underscores the importance of taking a multimodal approach for this critical area of research.