D. Oliveira, R. Silva Ferreira, et al.
EAGE/PESGB Workshop Machine Learning 2018
Understanding human movement is key to improving input devices and interaction techniques. This paper presents a study of mouse movements of motion-impaired users, with an aim to gaining a better understanding of impaired movement. The cursor trajectories of six motion-impaired users and three able-bodied users are studied according to their submovement structure. Performance measures based on submovement structure are described, including the frequency and duration of pauses between submovements, verification times, the number of submovements, the peak speed of submovements and the accuracy of submovements in two dimensions. The measures are shown to be sensitive to differences between users with dissimilar physical capabilities. Results include findings that some motion-impaired users pause more often and for longer than able-bodied users, require up to five times more submovements to complete the same task, and exhibit a greater decline in accuracy with increasing speed than able-bodied users. © 2005 Taylor & Francis Group Ltd.
D. Oliveira, R. Silva Ferreira, et al.
EAGE/PESGB Workshop Machine Learning 2018
Dimitrios Christofidellis, Giorgio Giannone, et al.
MRS Spring Meeting 2023
Thomas Erickson, Susan Herring, et al.
CHI EA 2002
Michael Heck, Masayuki Suzuki, et al.
INTERSPEECH 2017