Keywords
5'22", 21Mb
EdgeWrite is a new unistroke text entry method for handheld devices designed to provide high accuracy and stability of motion for people with motor impairments. It is also effective for able-bodied people. An EdgeWrite user enters text by traversing the edges and diagonals of a square hole imposed over the usual text input area. Gesture recognition is accomplished not through pattern recognition but through the sequence of corners that are hit. This means that the full stroke path is unimportant and recognition is highly deterministic, enabling better accuracy than other gestural alphabets such as Graffiti. A study of able-bodied users showed subjects with no prior experience were 18% more accurate during text entry with Edge Write than with Graffiti (p>.05), with no significant difference in speed. A study of 4 subjects with motor impairments revealed that some of them were unable to do Graffiti, but all of them could do Edge Write. Those who could do both methods had dramatically better accuracy with Edge Write.
Most of today's GUIs are designed for the typical, able-bodied user; atypical users are, for the most part, left to adapt as best they can, perhaps using specialized assistive technologies as an aid. In this paper, we present an alternative approach: SUPPLE++ automatically generates interfaces which are tailored to an individual's motor capabilities and can be easily adjusted to accommodate varying vision capabilities. SUPPLE++ models users. motor capabilities based on a onetime motor performance test and uses this model in an optimization process, generating a personalized interface. A preliminary study indicates that while there is still room for improvement, SUPPLE++ allowed one user to complete tasks that she could not perform using a standard interface, while for the remaining users it resulted in an average time savings of 20%, ranging from an slowdown of 3% to a speedup of 43%.
Most of today's GUIs are designed for the typical, able-bodied user; atypical users are, for the most part, left to adapt as best they can, perhaps using specialized assistive technologies as an aid. In this paper, we present an alternative approach: SUPPLE++ automatically generates interfaces which are tailored to an individual's motor capabilities and can be easily adjusted to accommodate varying vision capabilities. SUPPLE++ models users. motor capabilities based on a onetime motor performance test and uses this model in an optimization process, generating a personalized interface. A preliminary study indicates that while there is still room for improvement, SUPPLE++ allowed one user to complete tasks that she could not perform using a standard interface, while for the remaining users it resulted in an average time savings of 20%, ranging from an slowdown of 3% to a speedup of 43%.
Most of today's GUIs are designed for the typical, able-bodied user; atypical users are, for the most part, left to adapt as best they can, perhaps using specialized assistive technologies as an aid. In this paper, we present an alternative approach: SUPPLE++ automatically generates interfaces which are tailored to an individual's motor capabilities and can be easily adjusted to accommodate varying vision capabilities. SUPPLE++ models users. motor capabilities based on a onetime motor performance test and uses this model in an optimization process, generating a personalized interface. A preliminary study indicates that while there is still room for improvement, SUPPLE++ allowed one user to complete tasks that she could not perform using a standard interface, while for the remaining users it resulted in an average time savings of 20%, ranging from an slowdown of 3% to a speedup of 43%.
While graphical user interfaces have gained much popularity in recent years, there are situations when the need to use existing applications in a nonvisual modality is clear. Examples of such situations include the use of applications on hand-held devices with limited screen space (or even no screen space, as in the case of telephones), or users with visual impairments.
We have developed an architecture capable of transforming the graphical interfaces of existing applications into powerful intuitive nonvisual interfaces. Our system, called Mercator, provides new input and output techniques for working in the nonvisual domain. Navigation is accomplished by traversing a hierarchical tree representation of the interface structure. Output is primarily auditory, although other output modalities (such as tactile) can be used as well. The mouse, an inherently visually-oriented device, is replaced by keyboard and voice interaction.
Our system is currently in its third major revision. We have gained insight into both the nonvisual interfaces presented by our system and the architecture necessary to construct such interfaces. This architecture uses several novel techniques to efficiently and flexibly map graphical interfaces into new modalities.
