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    Age-specific predictive models of human performance
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    Abstract:
    Designers often struggle to create interfaces that are optimal for both younger and older adults, as they may interact differently with the same interface. Human-performance models have been used to aid designers in evaluating the efficiency of user interfaces. Can we create age-specific models to help designers create interfaces that are efficient for all age groups? We modeled a target acquisition task using published younger and older person parameters. While the younger model's mean prediction matches younger human data well (within 3.2%), the older model overestimates older users' mean task times by 34.6%. Further work should explore the influence of device type and the role of error-avoidance on parameter values for models of older adult interactions with technology.
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    Interface (matter)
    Assistive Robots have an inherent need of adapting to the user they are assisting. This is crucial for the correct development of the task, user safety, and comfort. However, adaptation can be performed in several manners. We believe user preferences are key to this adaptation. In this article, we evaluate the use of preferences for Physically Assistive Robotics tasks in a Human-Robot Interaction user evaluation. Three assistive tasks have been implemented consisting of assisted feeding, shoe-fitting, and jacket dressing, where the robot performs each task in a different manner based on user preferences. We assess the ability of the users to determine which execution of the task used their chosen preferences (if any). The obtained results show that most of the users were able to successfully guess the cases where their preferences were used even when they had not seen the task before. We also observe that their satisfaction with the task increases when the chosen preferences are employed. Finally, we also analyze the user’s opinions regarding assistive tasks and preferences, showing promising expectations as to the benefits of adapting the robot behavior to the user through preferences.
    User Satisfaction
    User needs
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    Interface (matter)
    Interface model
    While frailty is not an inevitable part of ageing it is more common in older people. Of people over the age of 65 years, 10% have frailty, which rises to between 25 and 50% of those over 85 (Clegg et al 2013). The British Geriatrics Society (BGS) (2014) Fit for Frailty guideline recommends that older people should be assessed for frailty at all healthcare encounters.
    Guideline
    Elderly people
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    Interface (matter)
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    Interface (matter)
    ITIES
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    Interface (matter)
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