Dealing with the effects of sensor displacement in wearable activity recognition Baños Legrán, Oresti Attila Toth, Mate Damas Hermoso, Miguel Pomares Cintas, Héctor Emilio Rojas Ruiz, Ignacio Activity recognition Sensor displacement Wearable sensors Inertial sensing Sensor fusion Human behavior inference Real-world 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. 2014-09-04T12:06:06Z 2014-09-04T12:06:06Z 2014 journal article Baños, O.; et al. Dealing with the effects of sensor displacement in wearable activity recognition. Sensors, 14(6): 9995-10023 (2014). [http://hdl.handle.net/10481/32906] 1424-8220 http://hdl.handle.net/10481/32906 10.3390/s140609995 eng info:eu-repo/grantAgreement/EC/FP7/228398 http://creativecommons.org/licenses/by-nc-nd/3.0/ open access Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License MDPI