Justyna Stępniak

Ms. Justyna Stępniak

Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Wileńska 4, 87-100 Toruń, Poland

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 January 2021 in Sensors
Verified
Journal Article
Open access
PDF file
NATALIA PAWLACZYKNATALIA PAWLACZYK
NATALIA PAWLACZYK
Magdalena SzmytkeMagdalena Szmytke
Magdalena Szmytke
MMMichał Meina
Michał Meina
MLMonika Lewandowska
Monika Lewandowska
JSJustyna Stępniak
Justyna Stępniak
JDJoanna Dreszer
Joanna Dreszer
A decline in the Spatial Navigation (SN) abilities has been observed in the course of healthy aging. Walking is an inseparable part of the navigation process; however, research tasks overlook this aspect in studies involving seniors. The present study was designed to overcome this limitation by recording gait parameters during natural environment navigation and to determine gait indicators that most accurately assign the participants to the proper age category. Thirteen elderly (mean age = 69.1 ± 5.4 year) and sixteen young women (mean age = 21.5 ± 2.2 year) equipped with gait sensors were asked to learn a path while walking in a real building (Learning Phase), reproduce the path (Memory Phase) and reach targets after a 30 min delay (Delayed Phase). The Receiver Operating Characteristics (ROC) analysis showed that our self-developed Gait Style Change indicator, that is, the difference in the probability of feet landing between particular SN task phases, classified the participants into either the elderly or the young group with the highest accuracy (0.91). The second most important indicator, the Task-Related (step counts in each SN task phase), achieved the accuracy discrimination of 0.83. The gait indicators, comprising single gait parameters measured while navigating, might be considered as accurately differentiating older from younger people.