Extending Fitts' law to two-dimensional tasks
CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Making computers easier for older adults to use: area cursors and sticky icons
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Beyond Fitts' law: models for trajectory-based HCI tasks
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Testing pointing device performance and user assessment with the ISO 9241, Part 9 standard
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Keyboard and mouse errors due to motor disabilities
International Journal of Human-Computer Studies
Quantitative analysis of scrolling techniques
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Machine Learning
Cursor measures for motion-impaired computer users
Proceedings of the fifth international ACM conference on Assistive technologies
Partitioning cursor movements in "point and click" tasks
CHI '03 Extended Abstracts on Human Factors in Computing Systems
Effect of age and Parkinson's disease on cursor positioning using a mouse
Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility
Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility
Developing steady clicks:: a method of cursor assistance for people with motor impairments
Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility
Dynamically adapting GUIs to diverse input devices
Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility
An evaluation of sticky and force enhanced targets in multi target situations
Proceedings of the 4th Nordic conference on Human-computer interaction: changing roles
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Dynamic detection of novice vs. skilled use without a task model
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Disruption and recovery of computing tasks: field study, analysis, and directions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
WebinSitu: a comparative analysis of blind and sighted browsing behavior
Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Automatically detecting pointing performance
Proceedings of the 13th international conference on Intelligent user interfaces
Understanding pointing problems in real world computing environments
Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility
PointAssist: helping four year olds point with ease
IDC '08 Proceedings of the 7th international conference on Interaction design and children
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The angle mouse: target-agnostic dynamic gain adjustment based on angular deviation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Automatically generating personalized user interfaces with Supple
Artificial Intelligence
Ability-Based Design: Concept, Principles and Examples
ACM Transactions on Accessible Computing (TACCESS)
Personalized dynamic accessibility
interactions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Accurate measurements of pointing performance from in situ observations
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Accurate pointing is an obstacle to computer access for individuals who experience motor impairments. One of the main barriers to assisting individuals with pointing problems is a lack of frequent and low-cost assessment of pointing ability. We are working to build technology to automatically assess pointing problems during every day (or real-world) computer use. To this end, we have gathered and studied real-world pointing use from individuals with motor impairments and older adults. We have used this data to develop novel techniques to analyze pointing performance. In this article, we present learned statistical models that distinguish between pointing actions from diverse populations using real-world pointing samples. We describe how our models could be used to support individuals with different abilities sharing a computer, or one individual who experiences temporary pointing problems. Our investigation contributes to a better understanding of real-world pointing. We hope that these techniques will be used to develop systems that can automatically adapt to users’ current needs in real-world computing environments.