Design and Development of the eBear: A Socially Assistive Robot for Elderly People with Depression

<p>There has been tremendous progress in the field of robotics in the past decade and especially developing humanoid robots with social abilities that can assist human at a socio-emotional level. The objective of this thesis is to develop and study a perceptive and expressive animal-like robot equipped with artificial intelligence in assisting the elderly people with depression. We investigated how social robots can become companions of elderly individuals with depression and improve their mood and increase their happiness and well-being. The robotic platform built in this thesis is a bear-like robot called the eBear. The eBear can show facial expression and head gesture, can understand user's emotion using audio-video sensory inputs and machine learning, can speak and show relatively accurate visual speech, and make dialog with users. the eBear can respond to their questions by querying the Internet, and even encourage them to physically be more active and even perform simple physical exercises. Besides building the robot, the eBear was used in running a pilot study in which seven elderly people with mild to severe depression interacted with the eBear for about 45 minutes three times a week over one month. The results of the study show that interacting with the eBear can increase happiness and mood of these human users as measured by Face Scale, and Geriatric Depression Scale (GDS) score systems. In addition, using Almere Model, it was concluded that the acceptance of the social agent increased over the study period. Videos of the users interaction with the eBear was analyzed and eye gaze, and facial expressions were manually annotated to better understand the behavior changes of users with the eBear. Results of these analyses as well as the exit surveys completed by the users at the end of the study demonstrate that a social robot such as the eBear can be an effective companion for the elderly people and can be a new approach for depression treatment.</p>

Name thesis:degree_name

M.S.

Level thesis:degree_level

Masters Thesis

Year dc:date.available

2016

Author dc:creator

• Kargarbideh, Amirhossein

Contributors dc:contributor

• Mohammad Mahoor, Ph.D.
• Timothy Sweeny
• Kimon Valavanis
• Matthew Rutherford

• Assistive technologies
• Robotics
• Socially assistive robotics
• Social robots
• Engineering

Statement dc:rights

• <p>Copyright is held by the author. User is responsible for all copyright compliance.</p>

Language dc:language

en

Repository record dc:identifier

https://digitalcommons.du.edu/etd/1101

OAI identifier oai:identifier

oai:digitalcommons.du.edu:etd-2101