Towards intelligent, adaptive input devices for users with physical disabilities

This thesis presents a novel application of user modelling, the domain of interest being the physical abilities of the user of a computer input device. Specifically, it describes a model which identifies aspects of keyboard use with which the user has difficulty. The model is based on data gathered in an empirical study of keyboard and mouse use by people with and without motor disabilities. In this study, many common input errors due to physical inaccuracies in using keyboards and mice were observed. For the majority of these errors, there exist keyboard or mouse configuration facilities intended to reduce or eliminate them. While such facilities are now integrated into the majority of modem operating systems, there is little published data describing their effect on keyboard or mouse usability. This thesis offers evidence that they can be extremely useful, even essential, but that further research and interface development are required. This thesis presents a user model which focuses on four of the most commonly observed keyboard difficulties. The model also makes recommendations for settings for three keyboard configuration facilities, each of which tackle one of these specific difficulties. As a user modelling task, this application presents a number of interesting challenges. Different users will have very different configuration requirements, and the requirements of individual users may also change over long or short periods of time. Some users will have cognitive impairments. Users may have very limited time and energy to devote to computer use. In response, this research has investigated the extent to which it is possible to model users without interrupting the task for which they are using a computer in the first place. This approach is appealing because it does not require users to spend time participating in model instantiation. This focus on inference rather than explicit testing or questioning also allows the model to dynamically track an individual user's changing requirements. This thesis shows that within the context of the keyboard difficulties studied, such an approach is feasible. The implemented model records users' keyboard input unintrusiveiy as they perform their own input tasks. This input is examined for evidence of certain types of input error or indications of difficulties in using the keyboard. In the model presented, conclusions are based on the assumption that the user is typing English text in a word processing application. However, the design of the model allows any other textual language to be used. A second empirical study, evaluating the model, is described. The model is shown to be very accurate in identifying users having difficulties in each of the areas tackled, the only exception being those who find a given operation awkward, but are able to perform it accurately. Where it is also possible to evaluate the configuration recommendations made by the model, the chosen settings are effective in reducing input errors and increasing user satisfaction with the keyboard. The model is also able to draw conclusions quickly for users with higher error rates, and shows good overall stability. In the light of this successful identification of keyboard difficulties, potential applications of the model are suggested. It could be used to help occupational therapists and assistive technologists to assess the keyboard configuration requirements of a new user. It could also be made available to users themselves - many people are currently unaware of facilities they may find useful, and how to activate them. The model could be extended to other areas of keyboard use, and to other input devices. This would allow systems to provide automatic, dynamic support for configuration, which would go some way towards improving the accessibility of computer systems for people with motor disabilities

The Care Work of Access

Current approaches to AI and Assistive Technology (AT) often foreground task completion over other encounters such as expressions of care. Our paper challenges and complements such task-completion approaches by attending to the care work of access—the continual affective and emotional adjustments that people make by noticing and attending to one another. We explore how this work impacts encounters among people with and without vision impairments who complete tasks together. We find that bound up in attempts to get things done are concerns for one another and how well people are doing together. Reading this work through emerging disability studies and feminist STS scholarship, we account for two important forms of work that give rise to access: (1) mundane attunements and (2) noninnocent authorizations. Together these processes work as sensitizing concepts to help HCI scholars account for the ways that intelligent ATs both produce access while sometimes subverting people with disabilities

An Evaluation of Three Task Farm Interfaces EPCC-KTP-PUL-TN-I

The role of the PUL KTP is to provide programmers with a set of utilities supporting common parallel processing paradigms. Such utilities may have several different kinds of interface, ranging from the low-level procedural style, through to multiple-program-multiple-data (MPMD) and single-program-multiple-data (SPMD) skeletons. In order to compare the relative merits of these three different approaches, a classical task farm has been implemented in each style. The implementations, written on top of CS Tools, have been used to program a calculation of the boundary points of the Mandelbrot set, and the three resulting programs are compared. The observed qualities of each interface are then projected onto more complex scenarios, resulting in a recommendation as to the most useful direction for PUL to follow. Contents 1 Introduction 3 2 The Interfaces 4 2.1 The Procedural Interface : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.2 The Multiple-Program-Multiple-Data Skeleton..

Effect of age and Parkinson's disease on cursor positioning using a mouse

Point-and-click tasks are known to present difficulties to users with physical impairments, particularly motor- or vision-based, and to older adults. This paper presents the results of a study to quantify and understand the effects of age and impairment on the ability to perform such tasks. Results from four separate user groups are presented and compared using metrics that describe the features of the movements made. Distinct differences in behaviour between all of the user groups are observed and the reasons for those differences are discussed