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 8.4mW 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.
Originalsprache | englisch |
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Seiten | 9-16 |
Seitenumfang | 8 |
DOIs | |
Publikationsstatus | Veröffentlicht - 15 Dez. 2017 |
Veranstaltung | 23rd IEEE International Conference on Parallel and Distributed Systems (ICPADS) - Shenzen, China Dauer: 15 Dez. 2017 → 17 Dez. 2017 http://futurenet.szu.edu.cn/icpads2017/?index.html |
Konferenz
Konferenz | 23rd IEEE International Conference on Parallel and Distributed Systems (ICPADS) |
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Land/Gebiet | China |
Ort | Shenzen |
Zeitraum | 15/12/17 → 17/12/17 |
Internetadresse |
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Best Paper Award
Saukh, Olga (Empfänger/-in), 17 Dez. 2017
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