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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 23/2020

22.07.2020 | S.I. : Emerging applications of Deep Learning and Spiking ANN

Affective analysis of patients in homecare video-assisted telemedicine using computational intelligence

verfasst von: A. Kallipolitis, M. Galliakis, A. Menychtas, I. Maglogiannis

Erschienen in: Neural Computing and Applications | Ausgabe 23/2020

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Abstract

The affective/emotional status of patients is strongly connected to the healing process and their health. Therefore, being aware of the psychological peaks and troughs of a patient provides the advantage of timely intervention by specialists or closely related kinsfolk. In this context, this paper presents the design and implementation of an emotion analysis module integrated in an existing telemedicine platform. Two different methodologies are utilized and discussed. The first scheme exploits the fast and consistent properties of the speeded-up robust features algorithm in order to identify the existence of seven different sentiments in human faces. The second is based on convolutional neural networks. The whole functionality is provided as a Web service for the healthcare platform during regular video teleconference sessions between authorized medical personnel and patients. The paper discusses the technical details of the implementation and the incorporation of the proposed scheme and provides the initial results of its accuracy and operation in practice.
Vorheriger Artikel Emerging applications of Deep Learning and Spiking ANN
Nächster Artikel Online meta-learning firewall to prevent phishing attacks

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Metadaten
Titel
Affective analysis of patients in homecare video-assisted telemedicine using computational intelligence
verfasst von
A. Kallipolitis
M. Galliakis
A. Menychtas
I. Maglogiannis
Publikationsdatum
22.07.2020
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 23/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-05203-z

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