Research Publications Authored by SLIIT Staff

Now showing 1 - 4 of 4

Embargo
Improved robot attitudes and emotions at a retirement home after meeting a robot
(IEEE, 2010-09-13) Stafford, R. Q; Broadbent, E; Jayawardena, C; Unger, U; Kuo, I. H; Igic, A; Wong, R; Kerse, N; Watson, C; MacDonald, B. A
This study investigated whether attitudes and emotions towards robots predicted acceptance of a healthcare robot in a retirement village population. Residents (n = 32) and staff (n = 21) at a retirement village interacted with a robot for approximately 30 minutes. Prior to meeting the robot, participants had their heart rate and blood pressure measured. The robot greeted the participants, assisted them in taking their vital signs, performed a hydration reminder, told a joke, played a music video, and asked some questions about falls and medication management. Participants were given two questionnaires; one before and one after interacting with the robot. Measures included in both questionnaires were the Robot Attitude Scale (RAS) and the Positive and Negative Affect Schedule (PANAS). After using the robot, participants rated the overall quality of the robot interaction. Both residents and staff reported more favourable attitudes (p <; .05) and decreases in negative affect (p <; .05) towards the robot after meeting it, compared with before meeting it. Pre-interaction emotions and robot attitudes, combined with post-interaction changes in emotions and robot attitudes, were highly predictive of participants' robot evaluations (R = .88, p <; .05). The results suggest both pre-interaction emotions and attitudes towards robots, as well as experience with the robot, are important areas to monitor and address in influencing acceptance of healthcare robots in retirement village residents and staff. The results support an active cognition model that incorporates a feedback loop based on re-evaluation after experience.
Embargo
Socially Assistive Robot HealthBot: Design, Implementation, and Field Trials
(IEEE, 2016-09-01) Jayawardena, C; Kuo, I. H; Broadbent, E; MacDonald, B. A
Socially assistive robotics is an important emerging research area. Socially assistive robotics is challenging as it is required to move robots out of laboratories and industrial settings to interact with ordinary human beings as peers, which requires social skills. The design process usually requires multidisciplinary research teams, which may comprise subject matter experts from various domains such as robotics, systems integration, medicine, psychology, gerontology, social and cognitive sciences, and neuroscience, among many others. Unlike most other robotic applications, socially assistive robotics faces some unique software and systems integration challenges. In this paper, the HealthBot robot architecture, which was designed to overcome these challenges, is presented. The presented architecture was implemented and used in several field trials. The details of the field trials are presented, and lessons learned are discussed with field trial results.
Embargo
Design, implementation and field tests of a socially assistive robot for the elderly: Healthbot version 2
(IEEE, 2012-06-24) Jayawardena, C; Kuo, I; Datta, C; Stafford, R.Q; Broadbent, E; MacDonald, B. A
This paper presents the second version of a mobile service robot (HealthBot) designed for older people. The lessons learned from studies of the first version of the robot at a retirement village, and design decisions for the second version, are discussed. Technical requirements of field trials, a focus on cognitive human-robot interactions, the importance of working together in a multidisciplinary team, and the necessity for rapid iterative development suggested a new software framework. The features of new framework are discussed and implementation details are presented. Details of field trials and user acceptance results are presented. Results are promising for older-user acceptance of the robot.
Embargo
Improved robot attitudes and emotions at a retirement home after meeting a robot
(IEEE, 2010-09-13) Stafford, R. Q; Broadbent, E; Jayawardena, C; Unger, U; Kuo, I. H; Igic, A; Wong, R; Kerse, N; Watson, C; MacDonald, B. A
This study investigated whether attitudes and emotions towards robots predicted acceptance of a healthcare robot in a retirement village population. Residents (n = 32) and staff (n = 21) at a retirement village interacted with a robot for approximately 30 minutes. Prior to meeting the robot, participants had their heart rate and blood pressure measured. The robot greeted the participants, assisted them in taking their vital signs, performed a hydration reminder, told a joke, played a music video, and asked some questions about falls and medication management. Participants were given two questionnaires; one before and one after interacting with the robot. Measures included in both questionnaires were the Robot Attitude Scale (RAS) and the Positive and Negative Affect Schedule (PANAS). After using the robot, participants rated the overall quality of the robot interaction. Both residents and staff reported more favourable attitudes (p <; .05) and decreases in negative affect (p <; .05) towards the robot after meeting it, compared with before meeting it. Pre-interaction emotions and robot attitudes, combined with post-interaction changes in emotions and robot attitudes, were highly predictive of participants' robot evaluations (R = .88, p <; .05). The results suggest both pre-interaction emotions and attitudes towards robots, as well as experience with the robot, are important areas to monitor and address in influencing acceptance of healthcare robots in retirement village residents and staff. The results support an active cognition model that incorporates a feedback loop based on re-evaluation after experience.

Research Publications Authored by SLIIT Staff

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