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Sensors 2017, 17(8), 1838; https://doi.org/10.3390/s17081838

Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors

Department of Electrical and Electronics Engineering, Bilkent University, Bilkent, Ankara 06800, Turkey
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Received: 14 July 2017 / Revised: 2 August 2017 / Accepted: 3 August 2017 / Published: 9 August 2017
(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications)
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Abstract

Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative transformations to remove the effect of absolute sensor orientation from the raw sensor data. We test the proposed methodology in activity recognition with four state-of-the-art classifiers using five publicly available datasets containing various types of human activities acquired by different sensor configurations. While the ordinary activity recognition system cannot handle incorrectly oriented sensors, the proposed transformations allow the sensors to be worn at any orientation at a given position on the body, and achieve nearly the same activity recognition performance as the ordinary system for which the sensor units are not rotatable. The proposed techniques can be applied to existing wearable systems without much effort, by simply transforming the time-domain sensor data at the pre-processing stage. View Full-Text
Keywords: human activity recognition; wearable sensing; sensor orientation; orientation-invariant sensing; motion sensors; inertial sensors; accelerometer; gyroscope; magnetometer; singular value decomposition; machine learning; Bayesian decision making; k-nearest-neighbor classifier; support vector machines; artificial neural networks human activity recognition; wearable sensing; sensor orientation; orientation-invariant sensing; motion sensors; inertial sensors; accelerometer; gyroscope; magnetometer; singular value decomposition; machine learning; Bayesian decision making; k-nearest-neighbor classifier; support vector machines; artificial neural networks
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Yurtman, A.; Barshan, B. Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors. Sensors 2017, 17, 1838.

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