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Improving wearable sensor data quality using context markers

Published:09 September 2019Publication History

ABSTRACT

A major challenge in human activity recognition over long periods with multiple sensors is clock synchronization of independent data streams. Poor clock synchronization can lead to poor data and classifiers. In this paper, we propose a hybrid synchronization approach that combines NTP (Network Time Protocol) and context markers. Our evaluation shows that our approach significantly reduces synchronization error (20 ms) when compared to approaches that rely solely on NTP or sensor events. Our proposed approach can be applied to any wearable sensor where an independent sensor stream requires synchronization.

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    • Published in

      cover image ACM Conferences
      UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
      September 2019
      1234 pages
      ISBN:9781450368698
      DOI:10.1145/3341162

      Copyright © 2019 ACM

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      Publication History

      • Published: 9 September 2019

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