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Please use this identifier to cite or link to this item: http://hdl.handle.net/10481/28450

Title: On the Use of Sensor Fusion to Reduce the Impact of Rotational and Additive Noise in Human Activity Recognition
Authors: Baños Legrán, Oresti
Damas Hermoso, Miguel
Pomares Cintas, Héctor
Rojas Ruiz, Ignacio
Issue Date: 2012
Abstract: The main objective of fusion mechanisms is to increase the individual reliability of the systems through the use of the collectivity knowledge. Moreover, fusion models are also intended to guarantee a certain level of robustness. This is particularly required for problems such as human activity recognition where runtime changes in the sensor setup seriously disturb the reliability of the initial deployed systems. For commonly used recognition systems based on inertial sensors, these changes are primarily characterized as sensor rotations, displacements or faults related to the batteries or calibration. In this work we show the robustness capabilities of a sensor-weighted fusion model when dealing with such disturbances under different circumstances. Using the proposed method, up to 60% outperformance is obtained when a minority of the sensors are artificially rotated or degraded, independent of the level of disturbance (noise) imposed. These robustness capabilities also apply for any number of sensors affected by a low to moderate noise level. The presented fusion mechanism compensates the poor performance that otherwise would be obtained when just a single sensor is considered.
Sponsorship: This work was supported in part by the Spanish CICYT Project TIN2007-60587, Junta de Andalucia Projects P07-TIC-02768 and P07-TIC-02906, the CENIT project AmIVital, of the “Centro para el Desarrollo Tecnol´ogico Industrial” (CDTI- Spain), the FPU Spanish grant AP2009-2244 and the UGR Spanish grant “Iniciaci´on a la Investigaci´on 2010/2011”.
Publisher: MDPI
Description: This article belongs to the Special Issue Select papers from UCAmI 2011 - the 5th International Symposium on Ubiquitous Computing and Ambient Intelligence (UCAmI'11).
Keywords: Activity recognition
Rotational noise
Additive noise
Metaclassifier
Accelerometer
Sensor fusion
URI: http://hdl.handle.net/10481/28450
ISSN: 1424-8220
Rights : Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License
Citation: Baños, O.; et al. On the Use of Sensor Fusion to Reduce the Impact of Rotational and Additive Noise in Human Activity Recognition. Sensors, 12(6): 8039-8054 (2012). [http://hdl.handle.net/10481/28450]
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