OESense: Employing occlusion effect for in-ear human sensing

Smart earbuds are recognized as a new wearable platform for personal-scale human motion sensing. However, due to the interference from head movement or background noise, commonly-used modalities (e.g. accelerometer and microphone) fail to reliably detect both intense and light motions. To obviate th...

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Main Authors: MA, Dong, FERLINI, Andrea, MASCOLO, Cecilia
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Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/7005
https://ink.library.smu.edu.sg/context/sis_research/article/8008/viewcontent/3458864.3467680.pdf
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spelling sg-smu-ink.sis_research-80082022-03-17T15:14:05Z OESense: Employing occlusion effect for in-ear human sensing MA, Dong FERLINI, Andrea MASCOLO, Cecilia Smart earbuds are recognized as a new wearable platform for personal-scale human motion sensing. However, due to the interference from head movement or background noise, commonly-used modalities (e.g. accelerometer and microphone) fail to reliably detect both intense and light motions. To obviate this, we propose OESense, an acoustic-based in-ear system for general human motion sensing. The core idea behind OESense is the joint use of the occlusion effect (i.e., the enhancement of low-frequency components of bone-conducted sounds in an occluded ear canal) and inward-facing microphone, which naturally boosts the sensing signal and suppresses external interference. We prototype OESense as an earbud and evaluate its performance on three representative applications, i.e., step counting, activity recognition, and hand-to-face gesture interaction. With data collected from 31 subjects, we show that OESense achieves 99.3% step counting recall, 98.3% recognition recall for 5 activities, and 97.0% recall for five tapping gestures on human face, respectively. We also demonstrate that OESense is compatible with earbuds’ fundamental functionalities (e.g. music playback and phone calls). In terms of energy, OESense consumes 746 mW during data recording and recognition and it has a response latency of 40.85 ms for gesture recognition. Our analysis indicates such overhead is acceptable and OESense is potential to be integrated into future earbuds. 2021-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7005 info:doi/10.1145/3458864.3467680 https://ink.library.smu.edu.sg/context/sis_research/article/8008/viewcontent/3458864.3467680.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Human-centered computing Ubiquitous and mobile computing systems and tools Artificial Intelligence and Robotics Databases and Information Systems
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Human-centered computing
Ubiquitous and mobile computing systems and tools
Artificial Intelligence and Robotics
Databases and Information Systems
spellingShingle Human-centered computing
Ubiquitous and mobile computing systems and tools
Artificial Intelligence and Robotics
Databases and Information Systems
MA, Dong
FERLINI, Andrea
MASCOLO, Cecilia
OESense: Employing occlusion effect for in-ear human sensing
description Smart earbuds are recognized as a new wearable platform for personal-scale human motion sensing. However, due to the interference from head movement or background noise, commonly-used modalities (e.g. accelerometer and microphone) fail to reliably detect both intense and light motions. To obviate this, we propose OESense, an acoustic-based in-ear system for general human motion sensing. The core idea behind OESense is the joint use of the occlusion effect (i.e., the enhancement of low-frequency components of bone-conducted sounds in an occluded ear canal) and inward-facing microphone, which naturally boosts the sensing signal and suppresses external interference. We prototype OESense as an earbud and evaluate its performance on three representative applications, i.e., step counting, activity recognition, and hand-to-face gesture interaction. With data collected from 31 subjects, we show that OESense achieves 99.3% step counting recall, 98.3% recognition recall for 5 activities, and 97.0% recall for five tapping gestures on human face, respectively. We also demonstrate that OESense is compatible with earbuds’ fundamental functionalities (e.g. music playback and phone calls). In terms of energy, OESense consumes 746 mW during data recording and recognition and it has a response latency of 40.85 ms for gesture recognition. Our analysis indicates such overhead is acceptable and OESense is potential to be integrated into future earbuds.
format text
author MA, Dong
FERLINI, Andrea
MASCOLO, Cecilia
author_facet MA, Dong
FERLINI, Andrea
MASCOLO, Cecilia
author_sort MA, Dong
title OESense: Employing occlusion effect for in-ear human sensing
title_short OESense: Employing occlusion effect for in-ear human sensing
title_full OESense: Employing occlusion effect for in-ear human sensing
title_fullStr OESense: Employing occlusion effect for in-ear human sensing
title_full_unstemmed OESense: Employing occlusion effect for in-ear human sensing
title_sort oesense: employing occlusion effect for in-ear human sensing
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/sis_research/7005
https://ink.library.smu.edu.sg/context/sis_research/article/8008/viewcontent/3458864.3467680.pdf
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