Multisensor Data Fusion for Pedestrians in Spatial Disorientation

Developments in pedestrian positioning systems present a great potential to assist users with special needs, e.g., people with spatial disorientation issues. In a spatial disorientation episode a person hesitates about her/his surroundings or gets lost in otherwise familiar environments. Research in pedestrian dead reckoning has shown outstanding results about the user's position based on human locomotion patterns. In this paper, we leverage the great advances in the personal positioning field to explore the conditions of a user during a spatial disorientation episode. Here, the parameters commonly used in PDR are utilized to identify events in a spatial disorientation episode. In other words, parameters associated with the user's step are used to identify when the user walks with normal patterns or presents unusual walking patterns. Due to the lack of knowledge of events associated with SDE, experiments were conducted with the aim to observe the process to become disorientated; consequently, an empirical approach is presented. Since this is a preliminary study results were not conclusive, nevertheless, meaningful information was obtained during empirical observations in which a participant was completely immersive in a SDE.