Mobile devices are becoming ubiquitous and, sometimes, even extensions of ourselves. These devices are growing fast in terms of delivered computational power, storage capacity, battery duration, and built-in sensors. Time and again, we see headlines advertising new unforeseen applications leveraging this power, especially the sensors, for solving diverse problems, including fall detection, user’s activity recognition, location identification, or even user authentication based on the way of walking (gait).
In this paper, the authors focus on motion sensors and discuss how the provided data can be interpreted and transformed to better serve different purposes. They propose a method to process the data from such sensors that reduces the acquisition noise and possible artifacts, and turns the data invariant to the device’s position and the user’s movement direction. A new coordinate system referred to as user-centric is introduced, as opposed to the two most common coordinate systems used—the device and world-coordinate systems. The results show the importance of properly pre-processing the acquired data to enable more reliable applications underpinned by mobile sensors.
Ferreira, A., Santos, G., Rocha, A., & Goldenstein, S. (2017). User-Centric Coordinates for Applications Leveraging 3-Axis Accelerometer Data. IEEE Sensors Journal, 17(16), 5231-5243.