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Sensors 2014, 14(6), 9995-10023; doi:10.3390/s140609995

Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

1
Department of Computer Architecture and Computer Technology, Research Center for Information and Communications Technologies-University of Granada (CITIC-UGR), C/Calle Periodista RafaelGomez Montero 2, Granada E18071, Spain
2
Language and Speech Laboratory, University of the Basque Country, Paseo de la Universidad 5,Vitoria E01006, Spain
*
Author to whom correspondence should be addressed.
Received: 21 March 2014 / Revised: 12 May 2014 / Accepted: 27 May 2014 / Published: 6 June 2014
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Abstract

Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements. View Full-Text
Keywords: activity recognition; sensor displacement; wearable sensors; inertial sensing; sensor fusion; human behavior inference; real-world activity recognition; sensor displacement; wearable sensors; inertial sensing; sensor fusion; human behavior inference; real-world
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Banos, O.; Toth, M.A.; Damas, M.; Pomares, H.; Rojas, I. Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition. Sensors 2014, 14, 9995-10023.

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