Abstract
The attention towards robot-assisted therapies (RAT) had grown steadily in recent years particularly for patients with dementia. However, rehabilitation practice using humanoid robots for individuals with Mild Cognitive Impairment (MCI) is still a novel method for which the adherence mechanisms, indications and outcomes remain unclear. An effective computing represents a wide range of technological opportunities towards the employment of emotions to improve human-computer interaction. Therefore, the present study addresses the effectiveness of a system in automatically decode facial expression from video-recorded sessions of a robot-assisted memory training lasted two months involving twenty-one participants. We explored the robot’s potential to engage participants in the intervention and its effects on their emotional state. Our analysis revealed that the system is able to recognize facial expressions from robot-assisted group therapy sessions handling partially occluded faces. Results indicated reliable facial expressiveness recognition for the proposed software adding new evidence base to factors involved in Human-Robot Interaction (HRI). The use of a humanoid robot as a mediating tool appeared to promote the engagement of participants in the training program. Our findings showed positive emotional responses for females. Tasks affects differentially affective involvement. Further studies should investigate the training components and robot responsiveness.
Highlights
Emotions are relevant in all aspects of human life
During the whole memory training program, facial expressions have been recognized in percentage for all the sessions and for all the participants as follows: anger has been founded in the 7.24% of the frames, disgust has been identified in the 2.51% of the data analyzed, fear has been recognized in the 11.83% of the video corpus, happiness has been identified in the 16.95% of the frames analyzed, sadness has been recognized in the 14.31% of the data, surprise has been founded in the 3.64%, and, neutral has been identified in the 43.52% of the videos
The present paper addressed the issue of emotion recognition through facial expression using a method to automatically detect basic facial emotional expressions with handling of occlusions in the context of a rehabilitation memory program for individuals with Mild Cognitive Impairment (MCI)
Summary
Emotions are relevant in all aspects of human life. Few visual stimuli are as socially salient as the faces of humans. Emotional and social signals expressing additional information are essential With this aim, particular attention was devoted to quantifying the effectiveness of a social robot on well-being of training recipients. Particular attention was devoted to quantifying the effectiveness of a social robot on well-being of training recipients This was accomplished measuring spontaneous facial expressions with a software for automatic assessment of human-robot interaction decoding facial expressions [10]. Our research addresses affective expression in human-robot interactions exploiting video clips recorded during the 2-month of the previous study and analyzing facial expressions from the participants [43]. The system recognize facial expression in a group through a multi-face detector providing the clinical perspectives on memory training program assisted by a social robot for the elderly. It is able to decode human emotions, simulate emotions through the color of his eyes or the position of the body, recognize faces and model physical exercise for seniors [2, 46], and equipped to measure of health and environmental parameters [50]
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