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 language | English |
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Pages (from-to) | 500-506 |
Number of pages | 7 |
Journal | Journals of Gerontology - Series A Biological Sciences and Medical Sciences |
Volume | 74 |
Issue number | 4 |
Early online date | 30 Dec 2017 |
DOIs | |
Publication status | Published - 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