2014/06/06 by Oresti Baños, Máté Tóth, Miguel Damas +2 · 2 citations
Computer Science · Engineering · #Context-Aware Activity Recognition Systems #Advanced Sensor and Energy Harvesting Materials #Interactive and Immersive Displays
paper · pdf · doi:10.3390/s140609995
openalex publication_date 2014/06/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
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.