Home /Research /Wearable robot for mental health intervention
LEARNING

Wearable robot for mental health intervention

Ker-Jiun Wang, Caroline Yan Zheng

Year
2019
Citations
4
Access
Open access

Abstract

The theory of human touch that causes the body to release hormone oxytocin can be an effective treatment to alleviate depression and anxiety, such that the patients don't need to seek the help from consultants or drug medications to improve their mental conditions. In this paper, we have developed a wearable robot that mimic human affective touch to build social bonds and regulate emotion and cognitive functions. The touch-stimulated emotion can be measured by brainwaves from 4 EEG electrodes placed on the parietal, prefrontal and left and right temporal lobe regions of the brain. The novel Deep Learning emotion decoder has been designed to identify the human affective, non-affective and neutral emotions. It paves the way in the future to develop an intelligent self-adaptive robot that understands human emotions and adjusts its touch stimulation patterns accordingly to regulate human mental states and treat depression and anxiety problems.

Keywords

Wearable computerAnxietyRobotPsychologyHuman–robot interactionIntervention (counseling)CognitionMental healthElectroencephalographyCognitive psychology

Related papers

Browse all LEARNING papers