@inproceedings{c9126b941e364ea693188209aa7115d4,
title = "Obtaining experiential data on assistive technology device abandonment",
abstract = "There have been few studies of abandonment of Assistive Technology, typically based on surveys and best practices expertise. This paper describes the application of classic experience sampling techniques to gather timely information about mobility aiding assistive technology in day-to-day use especially with respect to causes of abandonment. The paper describes the technical understructure of the system, which uses smartphones to gather, and web services to store, data. Also described is the setup and branching of the question set presented on the smartphone. Beyond details of use of the assistive technology, the system collects a verified scale of responses to determine the emotional affect of the participant. Sampling is taken several times during the day by actively pushing a set of questions that are tailored to the users technology and responses. There is also provision for the participant to push the information to the system when desired.",
keywords = "Abandonment, Assistive technology, Experience sampling, Mobility aids",
author = "Helen Petrie and Stefan Carmien and Andrew Lewis",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 11th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCI 2017 ; Conference date: 09-07-2017 Through 14-07-2017",
year = "2017",
doi = "10.1007/978-3-319-58706-6\_18",
language = "English",
isbn = "9783319587059",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "217--226",
editor = "Margherita Antona and Constantine Stephanidis",
booktitle = "Universal Access in Human-Computer Interaction",
address = "Germany",
}