Analysis of free-living gait in older adults with and without Parkinson's disease and with and without a history of falls: Identifying generic and disease specific characteristics

Silvia Del Din, Brook Galna, Alan Godfrey, Esther Mj Bekkers, Elisa Pelosin, Freek Nieuwhof, Anat Mirelman, Jeffrey M Hausdorff, Lynn Rochester

Research output: Contribution to journalArticlepeer-review

123 Citations (Scopus)

Abstract

Background: Falls are associated with gait impairments in older adults (OA) and Parkinson's disease (PD). Current approaches for evaluating falls risk are based on self-report or one-time assessment and may be suboptimal. Wearable technology allows gait to be measured continuously in free-living conditions. The aim of this study was to explore generic and specific associations in free-living gait in fallers and non-fallers with and without PD.

Methods: 277 fallers (155 PD, 122 older adults (OA)) who fell twice or more in the previous 6 months and 65 non-fallers (15 PD, 50 OA) were tested. Free-living gait was characterised as the volume, pattern, and variability of ambulatory bouts (Macro), and 14 discrete gait characteristics (Micro). Macro and Micro variables were quantified from free-living data collected using an accelerometer positioned on the low back for one week.

Results: Macro variables showed that fallers walked with shorter and less variable ambulatory bouts than non-fallers, independent of pathology. Micro variables within ambulatory bouts showed fallers walked with slower, shorter and less variable steps than non-fallers. Significant interactions showed disease specific differences in variability with PD fallers demonstrating greater variability (step length) and OA fallers less variability (step velocity) than their non-faller counterparts (p<0.004).

Conclusions: Common and disease-specific changes in free-living Macro and Micro gait highlight generic and selective targets for intervention depending on type of faller (OA-PD). Our findings support free-living monitoring to enhance assessment. Future work is needed to confirm the optimal battery of measures, sensitivity to change and value for fall prediction.

Original languageEnglish
Pages (from-to)500-506
Number of pages7
JournalJournals of Gerontology - Series A Biological Sciences and Medical Sciences
Volume74
Issue number4
Early online date30 Dec 2017
DOIs
Publication statusPublished - Apr 2019

Keywords

  • Falls
  • gait
  • Parkinsons
  • wearable technology
  • Gait
  • Wearable Technology
  • Humans
  • Independent Living
  • Male
  • Case-Control Studies
  • Gait/physiology
  • Postural Balance/physiology
  • Aged, 80 and over
  • Parkinson Disease/complications
  • Female
  • Aged
  • Accelerometry
  • Accidental Falls

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