An early characterisation of wearing variability on motion signals for wearables

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An early characterisation of wearing variability on motion signals for wearables

Conference Paper (2019)

Author(s)

Chulhong Min (Nokia Bell Labs)

Akhil Mathur (University College London)

Alessandro Montanari (Nokia Bell Labs)

Fahim Kawsar (Nokia Bell Labs, TU Delft - Industrial Design Engineering)

Research Group

Knowledge and Intelligence Design

Wearable Motion sensing Wearing variability

DOI related publication

https://doi.org/10.1145/3341163.3347716 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:cd5d2da0-f56c-454e-805e-ffccb9935fb6

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Publication Year

2019

Language

English

Research Group

Knowledge and Intelligence Design

Pages (from-to)

166-168

Publisher

ACM

ISBN (electronic)

978-145036870-4

Event

2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2019 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2019 (2019-09-09 - 2019-09-13), London, United Kingdom

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156

Abstract

We explore a new variability observed in motion signals acquired from modern wearables. Wearing variability refers to the variations of the device orientation and placement across wearing events. We collect the accelerometer data on a smartwatch and an earbud and analyse how motion signals change due to the wearing variability. Our analysis shows that the wearing variability can bring an unexpected change to motion signals, not only from different users but also from different wearing sessions of the same user. We also provide empirical ranges of changes in device orientations.