Emotion-aware connected healthcare big data towards 5G

Abstract

The recent development of big data-oriented wireless technologies in terms of emerging 5G, edge computing, interconnected devices of the Internet of Things (IoT), and data analytics, as well as techniques, have enabled connected healthcare services for a happier and healthier life. Although, the quality of the healthcare services can be enhanced through big data-oriented wireless technologies, however, the challenges remain for not considering emotional care, especially for children, elderly, and mentally ill people. In this paper, we propose an emotion-aware connected healthcare system using a powerful emotion detection module. Different IoT devices are used to capture speech and image signals of a patient in a smart home scenario. These signals are used as the input to the emotion detection module. Speech and image signals are processed separately, and classification scores using these signals are fused to produce a final score to take a decision about the emotion. If the emotion is detected as pain, caregivers can visit the patient. Several experiments were performed to validate the proposed system, and good accuracies, up to 99.87%, were achieved for emotion detection. The proposed framework would greatly contribute personalized and seamless emotion-aware healthcare services toward 5G.