BARTON : Low power tongue movement sensing with in-ear barometers
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Detail(s)
Original language | English |
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Title of host publication | Proceedings - 2017 IEEE 23rd International Conference on Parallel and Distributed Systems, ICPADS 2017 |
Publisher | IEEE Computer Society |
Pages | 9-16 |
Volume | 2017-December |
ISBN (print) | 9781538621295 |
Publication status | Published - 29 May 2018 |
Externally published | Yes |
Publication series
Name | Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS |
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Volume | 2017-December |
ISSN (Print) | 1521-9097 |
Conference
Title | 23rd IEEE International Conference on Parallel and Distributed Systems, ICPADS 2017 |
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Place | China |
City | Shenzhen |
Period | 15 - 17 December 2017 |
Link(s)
Abstract
Sensing tongue movements enables various applications in hands-free interaction and alternative communication. We propose BARTON, a BARometer based low-power and robust TONgue movement sensing system. Using a low sampling rate of below 50 Hz, and only extracting simple temporal features from in-ear pressure signals, we demonstrate that it is plausible to distinguish important tongue gestures (left, right, forward) at low power consumption. We prototype BARTON with commodity earpieces integrated with COTS barometers for in-ear pressure sensing and an ARM micro-controller for signal processing. Evaluations show that BARTON yields 94% classification accuracy and 8.4 mW power consumption, which achieves comparable accuracy, but consumes 44 times lower energy than the state-of-the-art microphone-based solutions. BARTON is also robust to head movements and operates with music played directly from earphones. © 2017 IEEE.
Research Area(s)
- Human computer interaction, Pressure sensors, Ubiquitous computing
Bibliographic Note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
Citation Format(s)
BARTON: Low power tongue movement sensing with in-ear barometers. / Maag, Balz; Zhou, Zimu; Saukh, Olga et al.
Proceedings - 2017 IEEE 23rd International Conference on Parallel and Distributed Systems, ICPADS 2017. Vol. 2017-December IEEE Computer Society, 2018. p. 9-16 (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS; Vol. 2017-December).
Proceedings - 2017 IEEE 23rd International Conference on Parallel and Distributed Systems, ICPADS 2017. Vol. 2017-December IEEE Computer Society, 2018. p. 9-16 (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS; Vol. 2017-December).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review