Abstract
With the growth of the elder population, fall risk evaluation is crucial to prevent elders from serious injuries, as well as reduce related financial burdens. A balance assessment, timed up and go (TUG), has been widely used to estimate fall risk. The standardized TUG focuses on flat ground walking with no environmental variance. Therefore, it falls short of assessing an individual's gait adaptability. Being able to adjust steps in response to environmental changes, for example, needing to navigate around or over a child's toy left on the sidewalk, is essential to avoid fall risk and fundamental to community ambulation. To this end, we propose four environment-adapting TUGs designed to assess one's ability to adapt gait in complex environments and a compatible system named Smart Insole TUG (SITUG), which provides real-time, feature-rich, and ease-of-operation TUG analysis. Based on experimental results, SITUG is capable of extracting gait related spatial-temporal features with all mean accuracies over 92%. Besides, the system achieves a mean accuracy of 92.23% in segmenting five TUG phases.
| Original language | English |
|---|---|
| Article number | 8374873 |
| Pages (from-to) | 1298-1305 |
| Number of pages | 8 |
| Journal | IEEE Internet of Things Journal |
| Volume | 6 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2019 |
Keywords
- Gait analysis
- sensors
- signal processing
- wearable computers
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