Name
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.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3211960.3211970 | MobiSys '18: The 16th Annual International Conference on Mobile Systems, Applications, and Services
Munich
Germany
June, 2018 |
DocType | ISBN | Citations |
Conference | 978-1-4503-5842-2 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chulhong Min | 1 | 362 | 30.13 |
| Akhil Mathur | 2 | 101 | 15.10 |
| Fahim Kawsar | 3 | 909 | 80.24 |