Lossy Compression Methods for Performance-Restricted Wearable Devices
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comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/159451
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Title
Lossy Compression Methods for Performance-Restricted Wearable DevicesDate
2020Publisher
CEUR Workshop ProceedingsISSN
1613-0073Bibliographic citation
Klus, L., Lohan, E. S., Granell, C., & Nurmi, J. (2020). Lossy compression methods for performance-restricted wearable devices. In WiP Proceedings of the International Conference on Localization and GNSS (ICL-GNSS 2020). CEUR-WS.Type
info:eu-repo/semantics/conferenceObjectVersion
info:eu-repo/semantics/publishedVersionSubject
Abstract
With the increasing popularity, diversity, and utilization of wearable devices, the data transfer-andstorage efficiency becomes increasingly important. This paper evaluates a set of compression techniques regarding ... [+]
With the increasing popularity, diversity, and utilization of wearable devices, the data transfer-andstorage efficiency becomes increasingly important. This paper evaluates a set of compression techniques regarding their utilization in crowdsourced wearable data. Transform-based Discrete Cosine
Transform (DCT), interpolation-based Lightweight Temporal Compression (LTC) and dimensionality reduction-focused Symbolic Aggregate Approximation (SAX) were chosen as traditional methods.
Additionally, an altered SAX (ASAX) is proposed by the authors and implemented to overcome some
of the shortcomings of the traditional methods. As one of the most commonly measured entities in
wearable devices, heart rate data were chosen to compare the performance and complexity of the
selected compression methods. Main results suggest that best compression results are obtained with
LTC, which is also the most complex of the studied methods. The best performance-complexity
trade-off is achieved with SAX. Our proposed ASAX has the best dynamic properties among the
evaluated methods. [-]
Description
Part de la conferència:
10th International Conference on Localization and GNSS (ICL GNSS 2020) . Tampere (Finlandia)
Is part of
ICL-GNSS 2020 WiP Proceedings, June 02–04, 2020, Tampere, FinlandFunder Name
European Union
Project code
info:eu-repo/grantAgreement/EC/H2020/813278
Project title or grant
European Union’s Horizon 2020 Research and Innovation programme
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⃝c 2020 Copyright for this paper by its authors.
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess