Lessons learned from the deployment of a long-term autonomous robot as companion in physical therapy for older adults with dementia a mixed methods study

Hebesberger, Denise, Koertner, Tobias, Gisinger, Christoph , Pripfl, Juergen and Dondrup, Christian (2016) Lessons learned from the deployment of a long-term autonomous robot as companion in physical therapy for older adults with dementia a mixed methods study. In: Human-Robot Interaction (HRI), 2016 11th ACM/IEEE International Conference on, 7 - 10 March 2016, Christchurch, New Zealand.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

Abstract

The eldercare sector is a promising deployment area for robotics where robots can support staff and help to bridge the predicted staff-shortage. A requirement analysis showed that one field of robot-deployment could be supporting physical therapy of older adults with advanced dementia. To explore this possibility, a long-term autonomous robot was deployed as a walking group assistant at a care site for the first time. The robot accompanied two weekly walking groups for a month, offering visual and acoustic stimulation. Therapists' experience, the robot's influence on the dynamic of the group and the therapists' estimation of the robot's utility were assessed by a mixed methods design consisting of observations, interviews and rating scales. Findings suggest that a robot has the potential to enhance motivation, group coherence and also mood within the walking group. Furthermore, older adults show curiosity and openness towards the robot. However, robustness and reliability of the system must be high, otherwise technical problems quickly turn the robot from a useful assistant into a source of additional workload and exhaustion for therapists.

Keywords:Legged locomotion, Medical treatment, Dementia, Navigation, Observers, Entertainment industry, patient treatment, geriatrics, human-robot interaction, medical robotics, mobile robots
Subjects:H Engineering > H670 Robotics and Cybernetics
L Social studies > L510 Health & Welfare
Divisions:College of Science > School of Computer Science
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ID Code:27951
Deposited On:11 Aug 2017 11:30

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