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Sensors and Materials, Volume 32, Number 1(1) (2020)
Copyright(C) MYU K.K.
pp. 27-40
S&M2085 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2585
Published: January 9, 2020

Unknown On-Body Device Position Detection Based on Ensemble Novelty Detection [PDF]

Mitsuaki Saito and Kaori Fujinami

(Received September 2, 2019; Accepted October 29, 2019)

Keywords: novelty detection, smartphone, on-body device localization, ensemble learning

In recent years, on-body device position recognition has attracted a lot of attention from the ubiquitous computing community with a view to providing reliable services to users. The existing work has focused on the recognition of classes included in a training dataset, but handling a new position that the recognition system does not know is still impossible. The unknown position should be handled in an appropriate way to avoid incorrect behavior and adapt to each user’s way of carrying the device. In this article, we propose a new detection method based on the ensemble learning principle, in which the final results are obtained from a collection of judgments by a weak novelty detector. We devise a method of finding a threshold that maximizes overall accuracy, rather than a mere majority vote. This method is evaluated with three datasets and various conditions to confirm the effectiveness of ensemble novelty detection and the threshold estimation method.

Corresponding author: Mitsuaki Saito


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Cite this article
Mitsuaki Saito and Kaori Fujinami, Unknown On-Body Device Position Detection Based on Ensemble Novelty Detection, Sens. Mater., Vol. 32, No. 1, 2020, p. 27-40.



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