BARTON: Low power tongue movement sensing with in-ear barometers

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...

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Main Authors: MAAG, Balz, ZHOU, Zimu, SAUKH, Olga, THIELE, Lothar
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Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/sis_research/4829
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spelling sg-smu-ink.sis_research-58322020-01-16T09:18:03Z BARTON: Low power tongue movement sensing with in-ear barometers MAAG, Balz ZHOU, Zimu SAUKH, Olga THIELE, Lothar 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 stateof-the-art microphone-based solutions. BARTON is also robust to head movements and operates with music played directly from earphones. 2017-12-17T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/4829 info:doi/10.1109/ICPADS.2017.00013 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Human computer interaction Ubiquitous computing Pressure sensors Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Human computer interaction
Ubiquitous computing
Pressure sensors
Software Engineering
spellingShingle Human computer interaction
Ubiquitous computing
Pressure sensors
Software Engineering
MAAG, Balz
ZHOU, Zimu
SAUKH, Olga
THIELE, Lothar
BARTON: Low power tongue movement sensing with in-ear barometers
description 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 stateof-the-art microphone-based solutions. BARTON is also robust to head movements and operates with music played directly from earphones.
format text
author MAAG, Balz
ZHOU, Zimu
SAUKH, Olga
THIELE, Lothar
author_facet MAAG, Balz
ZHOU, Zimu
SAUKH, Olga
THIELE, Lothar
author_sort MAAG, Balz
title BARTON: Low power tongue movement sensing with in-ear barometers
title_short BARTON: Low power tongue movement sensing with in-ear barometers
title_full BARTON: Low power tongue movement sensing with in-ear barometers
title_fullStr BARTON: Low power tongue movement sensing with in-ear barometers
title_full_unstemmed BARTON: Low power tongue movement sensing with in-ear barometers
title_sort barton: low power tongue movement sensing with in-ear barometers
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/sis_research/4829
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