Software wizards to adjust keyboard and mouse settings for people with physical impairments

Designing an app for alternative access assessments: Using interviews to uncover and define user needs

To support effective alternative access assessment and service delivery for people with motor impairments, we are developing an app called Access Navigator. This paper describes the first stage of the project: the interviews we conducted as part of a discovery process to improve our understanding of user needs. We individually interviewed 8 assistive technology practitioners and 3 clients who use alternative access methods, to learn what practitioners were currently doing in their access assessments, identify opportunities for improving current practice, and understand what the assessment process was like for clients. We extracted 236 relevant quotes from interview transcripts, and clustered the quotes using the affinity wall method, yielding 42 themes. Here we present the 21 highest priority themes, along with the app requirements that support those themes. Results confirmed the need for a tool to support more effective assessments, with emphasis on taking the worry out of access assessments and supporting early success. Results also revealed specific needs such as flexible workflow, personalized test-drive tasks, and a choice of metrics (including client preference). With a richer understanding of user needs, we are in a much better position to design software that can address those needs.

Automatic Adjustment of Keyboard Settings Can Enhance Typing

We developed and evaluated a software tool for the automatic configuration of Windows keyboard settings. The software is intended to accommodate the needs of people with physical impairments, with a goal of improved productivity and comfort during typing. The prototype software, called AutoIDA, monitors user activity during performance of regular computer tasks and recommends the Sticky Keys and key repeat settings to meet the user's specific needs. The evaluation study included fourteen individuals with upper extremity impairments. AutoIDA recommended changes to the default keyboard settings for 10 of the 14 participants. For these individuals, average typing speed was essentially the same whether users typed with the default keyboard settings (5.5 wpm) or the AutoIDA-recommended settings (5.3 wpm). Average typing errors decreased with use of the recommended settings, from 17.6% to 13.3%, but this was not quite statistically significant (p = .10). On an individual basis, four participants appeared to improve their overall typing performance with AutoIDA-recommended settings. For more specific metrics, AutoIDA prevented about 90% of inadvertent key repeats (with a revised algorithm) and increased the efficiency and accuracy of entering modified (shifted) characters. Participants agreed that software like AutoIDA would be useful to them (average rating 4.1, where 5 = strongly agree).

Assistive technology use by disability type and race: exploration of a population-based health survey

PURPOSE

To examine the relationships among Assistive Technology (AT) use, race, type of disability and selected other demographic characteristics.

METHOD

Using 2009 National Health Interview Survey, descriptive statistics, statistical interactions and binary logistic regression were performed to identify, contrast and predict the likelihood of using AT based on the type of disability among African Americans (AAs) and European Americans (EAs).

RESULTS

We found that more AAs (10% within group proportion of total AAs) used AT compared to EAs (7.5% within group proportion of total EAs). Physical (p < 0.001), auditory (p = 0.028) and emotional (p = 0.008) impairments were statistically significant predictors of AT use. However, physical impairment as a predictor of AT use was greater among AAs (OR = 222.49, CI: 64.04-773.04, p < 0.001) than EAs (OR = 50.77, CI: 31.78-81.12, p < 0.001). EAs had a greater number of disabling conditions that predict the use of AT than AAs, whereas AAs had more demographic characteristics beyond race that predict AT use than EAs.

CONCLUSIONS

Disparities were observed in AT usage by disability types and demographic characteristics between AAs and EAs. Moreover, the predictive strength of AT usage based on disability types and other demographic variables differed by races. Overall, the findings about the different relationships among race, disability type, and AT use are found. Implications for Rehabilitation The finding may inform the development of initiatives by rehabilitation leaders to encourage the use of AT by AAs and EAs according to their type of impairment. Having identified physical impairment as statistically significant predictor of AT use greater among AAs, rehabilitation leaders should ensure that people living with those types of disability have access to the corresponding type of AT and can use them effectively.

Automatic Adjustment of Mouse Settings to Improve Pointing Performance

This article describes the development and evaluation of a software tool for the automatic configuration of mice and other pointing devices. The software is intended to accommodate the needs of people with physical impairments, with a goal of improved productivity and comfort during computer use. We successfully built prototype software that monitors user activity during performance of regular computer tasks and recommends appropriate Windows mouse settings to meet the user's specific needs. Twelve individuals with upper extremity impairments participated in an evaluation study. On average, the recommended settings significantly improved pointing performance for this subject group. The effect on trial time, entries, and error-free trials was significant at the 0.05 level. Trial time showed the strongest effect, improving by 29.3% with the settings recommended by our software. These results suggest that our software can successfully determine the appropriate mouse settings for an individual, yielding significant improvements in pointing performance.