Using smartphone accelerometry to assess the relationship between cognitive load and gait dynamics during outdoor walking

Simon Ho*, Amelia Mohtadi, Kash Daud, Ute Leonards, Todd Handy

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

5 Citations (Scopus)
229 Downloads (Pure)

Abstract

Research has demonstrated that an increase in cognitive load can result in increased gait variability and slower overall walking speed, both of which are indicators of gait instability. The external environment also imposes load on our cognitive systems; however, most gait research has been conducted in a laboratory setting and little work has demonstrated how load imposed by natural environments impact gait dynamics during outdoor walking. Across four experiments, young adults were exposed to varying levels of cognitive load while walking through indoor and outdoor environments. Gait dynamics were concurrently recorded using smartphone-based accelerometry. Results suggest that, during indoor walking, increased cognitive load impacted a range of gait parameters such as step time and step time variability. The impact of environmental load on gait, however, was not as pronounced, with increased load associated only with step time changes during outdoor walking. Overall, the present work shows that cognitive load is related to young adult gait during both indoor and outdoor walking, and importantly, smartphones can be used as gait assessment tools in environments where gait dynamics have traditionally been difficult to measure.

Original languageEnglish
Article number3119
Number of pages13
JournalScientific Reports
Volume9
DOIs
Publication statusPublished - 28 Feb 2019

Structured keywords

  • Visual Perception
  • Brain and Behaviour
  • Cognitive Science
  • Cognitive Neuroscience

Fingerprint Dive into the research topics of 'Using smartphone accelerometry to assess the relationship between cognitive load and gait dynamics during outdoor walking'. Together they form a unique fingerprint.

Cite this