Sensors, Vol. 20, Pages 6559: Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand

Sensors, Vol. 20, Pages 6559: Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand Sensors doi: 10.3390/s20226559 Authors: Markus Ebner Toni Fetzer Markus Bullmann Frank Deinzer Marcin Grzegorzek With the ubiquity of smartphones, the interest in indoor localization as a research area grew. Methods based on radio data are predominant, but due to the susceptibility of these radio signals to a number of dynamic influences, good localization solutions usually rely on additional sources of information, which provide relative information about the current location. Part of this role is often taken by the field of activity recognition, e.g., by estimating whether a pedestrian is currently taking the stairs. This work presents different approaches for activity recognition, considering the four most basic locomotion activities used when moving around inside buildings: standing, walking, ascending stairs, and descending stairs, as well as an additional messing around class for rejections. As main contribution, we introduce a novel approach based on analytical transformations combined with artificially constructed sensor channels, and compare that to two approaches adapted from existing literature, one based on codebooks, the other using statistical features. Data is acquired using accelerometer and gyroscope only. In addition to the most widely adopted use-case of carrying the smartphone in the trouser pockets, we will ...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research