Association between daily-life gait quality characteristics and physiological fall risk in older people

Sabine Schootemeijer, Roel H.A. Weijer, Marco J.M. Hoozemans, Kimberley S. van Schooten, Kim Delbaere, Mirjam Pijnappels*

*Corresponding author for this work

Research output: Contribution to JournalLetterAcademicpeer-review

Abstract

Gait quality characteristics obtained from accelerometry during daily life are predictive of falls in older people but it is unclear how they relate to fall risk. Our aim was to test whether these gait quality characteristics are associated with the severity of fall risk. We collected one week of trunk accelerometry data from 279 older people (aged 65–95 years; 69.5% female). We used linear regression to investigate the association between six daily-life gait quality characteristics and categorized physiological fall risk (QuickScreen). Logarithmic rate of divergence in the vertical (VT) and anteroposterior (AP) direction were significantly associated with the level of fall risk after correction for walking speed (both p < 0.01). Sample entropy in VT and the mediolateral direction and the gait quality composite were not significantly associated with the level of fall risk. We found significant differences between the high fall risk group and the very low-and low-risk groups, the moderate-and very low-risk and the moderate and low-risk groups for logarithmic rate of divergence in VT and AP (all p ≤ 0.01). We conclude that logarithmic rate of divergence in VT and AP are associated with fall risk, making them feasible to assess the physiological fall risk in older people.

Original languageEnglish
Article number5580
Pages (from-to)1-8
Number of pages8
JournalSensors (Switzerland)
Volume20
Issue number19
DOIs
Publication statusPublished - 29 Sep 2020

Keywords

  • Accelerometry
  • Accidental falls
  • Activity monitoring
  • Aged
  • Locomotion
  • Mobility
  • Wearable devices

Fingerprint

Dive into the research topics of 'Association between daily-life gait quality characteristics and physiological fall risk in older people'. Together they form a unique fingerprint.

Cite this