Research Papers - Dept of Information Technology
Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/593
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Publication Embargo A Comprehensive Mobile Platform for Fostering Communication, Literacy, Numeracy, and Emotion Understanding in Children with ASD(IEEE, 2024-07-25) Bandara, T.W.M.I.P.S; Deshan, M.A.D.; Prasanth, P.; Nadeera, M.S.; Krishara, JThis study presents SIPNENA, a novel mobile application designed to aid the learning and communication development of Sinhala-speaking autistic children aged six, particularly in rural areas of Sri Lanka. It offers a unique approach to teaching challenging subjects like English and Mathematics, tailored to the specific needs of children with Autism Spectrum Disorder (ASD). The application integrates interactive methodologies and gamification elements to facilitate better communication, understanding, and engagement. Additionally, it incorporates real-time emotion recognition features to monitor and respond to children's emotional states during learning activities. This research evaluates SIPNENA's effectiveness in improving communication abilities, academic skills, and emotion understanding among autistic children. The findings indicate promising results in catering to the unique educational needs of this target population, particularly in under-resourced rural regions, where specialized interventions are often scarce.Publication 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. AThis 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.Publication Embargo Teaching a tele-robot using natural language commands(IEEE, 2005-11-07) Jayawardena, C; Watanabe, K; Izumi, KFor Internet-based teleoperation systems, user-friendly natural interfaces are advantageous because those systems are intended to be used by non-experts. In developing user friendly interfaces, natural language communication is mandatory. This work presents a system in which a sub-set of natural language is used to command a tele-robot manipulator doing an object sorting task. The paper discusses about referring to objects with natural language commands such as "pick the small red cube". This is achieved by learning individual lexical symbols that refer to colors, shapes, and sizes independently, and then inferring the meaning of a combination of them.Publication 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. AThis 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.