Using audio cues to support motion gesture interaction on mobile devices

Motion gestures are an underutilized input modality for mobile interaction despite numerous potential advantages. Negulescu et al. found that the lack of feedback on attempted motion gestures made it difficult for participants to diagnose and correct errors, resulting in poor recognition performance and user frustration. In this paper, we describe and evaluate a training and feedback technique, Glissando, which uses audio characteristics to provide feedback on the systems interpretation of user input. This technique enables feedback by verbally confirming correct gestures and notifying users of errors in addition to providing continuous feedback by mapping distinct musical notes to each of three axes and manipulating pitch to specify both spatial and temporal information.

Name thesis:degree_name

Master of Science (M.S.)

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Computer Science

Grantor dc:publisher

Colorado State University. Libraries

Year dc:date.issued

2015

Authors dc:creator

• Morrison-Smith, Sarah, author
• Ruiz, Jaime, advisor
• Boucher, Christina, committee member
• Peterson, Chris, committee member

• human-computer interaction
• motion gestures
• mobile interaction
• audio feedback

Statement dc:rights

• Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.

Language dc:language.iso

eng, English

Identifier URI

https://doi.org/10.25675/3.018583

OAI identifier oai:identifier

oai:mountainscholar.org:10217/166911