Robotic Emotion Monitoring for Mental Health Applications: Preliminary Outcomes of a Survey - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Robotic Emotion Monitoring for Mental Health Applications: Preliminary Outcomes of a Survey

Résumé

Maintaining mental health is crucial for emotional, psychological, and social well-being. Currently, however, societal mental health is at an all-time low. Robots have already proven useful in medicine, and robot assisted mental therapies through emotional monitoring have great potential. This paper reviews 60 recent papers to determine how accurately robots can classify human emotions using the latest sensor technologies. Among 18 different signals, it was determined that EDA sensors are best for this application. Our findings also show that CNN outperforms SVM, SVR, KNN and LDA for classifying EDA data with an average of 79% accuracy. This is further improved with the addition of RGB sensor data.
Fichier principal
Vignette du fichier
520519_1_En_62_Chapter.pdf (392.02 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04291213 , version 1 (17-11-2023)

Licence

Paternité

Identifiants

Citer

Marat Rostov, Md Zakir Hossain, Jessica Sharmin Rahman. Robotic Emotion Monitoring for Mental Health Applications: Preliminary Outcomes of a Survey. 18th IFIP Conference on Human-Computer Interaction (INTERACT), Aug 2021, Bari, Italy. pp.481-485, ⟨10.1007/978-3-030-85607-6_62⟩. ⟨hal-04291213⟩
15 Consultations
4 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More