Prediction of disorientation by accelerometric and gait features in young and older adults navigating in a virtually enriched environment.

Autor/inn/en	Teipel, Stefan; Amaefule, Chimezie O.; Lüdtke, Stefan; Görß, Doreen; Faraza, Sofia; Bruhn, Sven; Kirste, Thomas
Titel	Prediction of disorientation by accelerometric and gait features in young and older adults navigating in a virtually enriched environment.
Quelle	In: Frontiers in psychology, 13 (2022) Art. 882446, 14 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Beigaben	Illustrationen
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	1664-1078
DOI	10.3389/fpsyg.2022.882446
Schlagwörter	Empirische Untersuchung; Experimentelle Untersuchung; Kognitiver Prozess; Alter; Deutschland; Erwachsener; Messung; Orientierung; Raum; Rostock; Stadt; Datenanalyse; Kognitiver Prozess; Videoaufzeichnung; Virtuelle Realität; Videoaufzeichnung; Orientierung; Stadt; Datenanalyse; Virtuelle Realität; Messung; Bewegung (Motorische); Alter; Raum; Erwachsener; Deutschland; Rostock
Abstract	Objective: To determine whether gait and accelerometric features can predict disorientation events in young and older adults. Methods: Cognitively healthy younger (18-40 years, n = 25) and older (60-85 years, n = 28) participants navigated on a treadmill through a virtual representation of the city of Rostock featured within the Gait Real-Time Analysis Interactive Lab (GRAIL) system. We conducted Bayesian Poisson regression to determine the association of navigation performance with domain-specific cognitive functions. We determined associations of gait and accelerometric features with disorientation events in real-time data using Bayesian generalized mixed effect models. The accuracy of gait and accelerometric features to predict disorientation events was determined using cross-validated support vector machines (SVM) and Hidden Markov models (HMM). Results: Bayesian analysis revealed strong evidence for the effect of gait and accelerometric features on disorientation. The evidence supported a relationship between executive functions but not visuospatial abilities and perspective taking with navigation performance. Despite these effects, the cross-validated percentage of correctly assigned instances of disorientation was only 72% in the SVM and 63% in the HMM analysis using gait and accelerometric features as predictors. Conclusion: Disorientation is reflected in spatiotemporal gait features and the accelerometric signal as a potentially more easily accessible surrogate for gait features. At the same time, such measurements probably need to be enriched with other parameters to be sufficiently accurate for individual prediction of disorientation events. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2023/1