Exploring Audio and Kinetic Sensing on Earable Devices

Chulhong Min; Akhil Mathur; Fahim Kawsar

doi:10.1145/3211960.3211970

Exploring Audio and Kinetic Sensing on Earable Devices

Chulhong Min, Akhil Mathur, Fahim Kawsar

Internet of Things

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

39 Citations (Scopus)

Abstract

In this paper, we explore audio and kinetic sensing on earable devices with the commercial on-the-shelf form factor. For the study, we prototyped earbud devices with a 6-axis inertial measurement unit and a microphone. We systematically investigate the differential characteristics of the audio and inertial signals to assess their feasibility in human activity recognition. Our results demonstrate that earable devices have a superior signal-to-noise ratio under the influence of motion artefacts and are less susceptible to acoustic environment noise. We then present a set of activity primitives and corresponding signal processing pipelines to showcase the capabilities of earbud devices in converting accelerometer, gyroscope, and audio signals into the targeted human activities with a mean accuracy reaching up to 88% in varying environmental conditions.

Original language	English
Title of host publication	WearSys 2018
Subtitle of host publication	Proceedings of the 4th ACM Workshop on Wearable Systems and Applications
Place of Publication	New York, NY
Publisher	Association for Computing Machinery (ACM)
Pages	5-10
Number of pages	6
ISBN (Print)	978-1-4503-5842-2
DOIs	https://doi.org/10.1145/3211960.3211970
Publication status	Published - 2018
Event	4th ACM Workshop on Wearable Systems and Applications, WearSys 2018: The 4th ACM Workshop on Wearable Systems and Applications - Munich, Germany Duration: 10 Jun 2018 → 10 Jun 2018 Conference number: 4th

Conference

Conference	4th ACM Workshop on Wearable Systems and Applications, WearSys 2018
Abbreviated title	WearSys 2018
Country/Territory	Germany
City	Munich
Period	10/06/18 → 10/06/18

Keywords

Audio sensing
Earable
Earbud
Kinetic sensing

Access to Document

10.1145/3211960.3211970

Cite this

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title = "Exploring Audio and Kinetic Sensing on Earable Devices",

abstract = "In this paper, we explore audio and kinetic sensing on earable devices with the commercial on-the-shelf form factor. For the study, we prototyped earbud devices with a 6-axis inertial measurement unit and a microphone. We systematically investigate the differential characteristics of the audio and inertial signals to assess their feasibility in human activity recognition. Our results demonstrate that earable devices have a superior signal-to-noise ratio under the influence of motion artefacts and are less susceptible to acoustic environment noise. We then present a set of activity primitives and corresponding signal processing pipelines to showcase the capabilities of earbud devices in converting accelerometer, gyroscope, and audio signals into the targeted human activities with a mean accuracy reaching up to 88% in varying environmental conditions.",

keywords = "Audio sensing, Earable, Earbud, Kinetic sensing",

author = "Chulhong Min and Akhil Mathur and Fahim Kawsar",

year = "2018",

doi = "10.1145/3211960.3211970",

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booktitle = "WearSys 2018",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "4th ACM Workshop on Wearable Systems and Applications, WearSys 2018 : The 4th ACM Workshop on Wearable Systems and Applications , WearSys 2018 ; Conference date: 10-06-2018 Through 10-06-2018",

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Min, C, Mathur, A & Kawsar, F 2018, Exploring Audio and Kinetic Sensing on Earable Devices. in WearSys 2018 : Proceedings of the 4th ACM Workshop on Wearable Systems and Applications. Association for Computing Machinery (ACM), New York, NY, pp. 5-10, 4th ACM Workshop on Wearable Systems and Applications, WearSys 2018, Munich, Germany, 10/06/18. https://doi.org/10.1145/3211960.3211970

Exploring Audio and Kinetic Sensing on Earable Devices. / Min, Chulhong; Mathur, Akhil; Kawsar, Fahim.
WearSys 2018 : Proceedings of the 4th ACM Workshop on Wearable Systems and Applications. New York, NY: Association for Computing Machinery (ACM), 2018. p. 5-10.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Exploring Audio and Kinetic Sensing on Earable Devices

AU - Min, Chulhong

AU - Mathur, Akhil

AU - Kawsar, Fahim

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PY - 2018

Y1 - 2018

N2 - In this paper, we explore audio and kinetic sensing on earable devices with the commercial on-the-shelf form factor. For the study, we prototyped earbud devices with a 6-axis inertial measurement unit and a microphone. We systematically investigate the differential characteristics of the audio and inertial signals to assess their feasibility in human activity recognition. Our results demonstrate that earable devices have a superior signal-to-noise ratio under the influence of motion artefacts and are less susceptible to acoustic environment noise. We then present a set of activity primitives and corresponding signal processing pipelines to showcase the capabilities of earbud devices in converting accelerometer, gyroscope, and audio signals into the targeted human activities with a mean accuracy reaching up to 88% in varying environmental conditions.

AB - In this paper, we explore audio and kinetic sensing on earable devices with the commercial on-the-shelf form factor. For the study, we prototyped earbud devices with a 6-axis inertial measurement unit and a microphone. We systematically investigate the differential characteristics of the audio and inertial signals to assess their feasibility in human activity recognition. Our results demonstrate that earable devices have a superior signal-to-noise ratio under the influence of motion artefacts and are less susceptible to acoustic environment noise. We then present a set of activity primitives and corresponding signal processing pipelines to showcase the capabilities of earbud devices in converting accelerometer, gyroscope, and audio signals into the targeted human activities with a mean accuracy reaching up to 88% in varying environmental conditions.

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KW - Earbud

KW - Kinetic sensing

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M3 - Conference contribution

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ER -

Exploring Audio and Kinetic Sensing on Earable Devices

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Keywords

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