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Predicting Pointing Time from Hand Strength

Authors: Pradipta Biswas; Peter Robinson 0001;

Predicting Pointing Time from Hand Strength

Abstract

Pointing tasks form a significant part of human-computer interaction in graphical user interfaces. We have developed a model to predict the task completion time for pointing tasks for people with motor-impairment. As part of the model, we have also developed a new scale of characterizing the extent of disability of users by measuring their grip strength. We have validated the model by conducting two trials involving people with motor-impairment and in both trials the model has predicted pointing time with statistically significant accuracy.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
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