Eight-Week Remote Monitoring Using a Freely Worn Device Reveals Unstable Gait Patterns in Older Fallers

被引:74
作者
Brodie, Matthew A. [1 ]
Lord, Stephen R. [1 ]
Coppens, Milou J. [2 ]
Annegarn, Janneke [3 ]
Delbaere, Kim [1 ]
机构
[1] Univ New S Wales, Neurosci Res Australia, Sydney, NSW, Australia
[2] Univ Groningen, Univ Med Ctr Groningen, Ctr Human Movement Sci, NL-9700 AB Groningen, Netherlands
[3] Philips Res Europe, Rochester, NY USA
关键词
Accelerometers; activity; cadence; daily; distribution; exposure; falls; gait; monitoring; older; patterns; people; remote; sensor; variability; walking; wearable; PHYSICAL-ACTIVITY; ACCELERATION PATTERNS; PARKINSONS-DISEASE; ACCELEROMETER; RISK; PEOPLE; PELVIS; SENSOR; HEAD; ASSOCIATION;
D O I
10.1109/TBME.2015.2433935
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objectives: Develop algorithms to detect gait impairments remotely using data from freely worn devices during long-term monitoring. Identify statistical models that describe how gait performances are distributed over several weeks. Determine the data window required to reliably assess an increased propensity for falling. Methods: 1085 days of walking data were collected from eighteen independent-living older people (mean age 83 years) using a freely worn pendant sensor (housing a triaxial accelerometer and pressure sensor). Statistical distributions from several accelerometer-derived gait features (encompassing quantity, exposure, intensity, and quality) were compared for those with and without a history of falling. Results: Participants completed more short walks relative to long walks, as approximated by a power law. Walks less than 13.1 s comprised 50% of exposure to walking-related falls. Daily-life cadence was bimodal and step-time variability followed a log-normal distribution. Fallers took significantly fewer steps per walk and had relatively more exposure from short walks and greatermode of step-time variability. Conclusions: Using a freely worn device and wavelet-based analysis tools allowed long-term monitoring of walks greater than or equal to three steps. In older people, short walks constitute a large proportion of exposure to falls. To identify fallers, mode of variability may be a better measure of central tendency than mean of variability. A week's monitoring is sufficient to reliably assess the long-term propensity for falling. Significance: Statistical distributions of gait performances provide a reference for future wearable device development and research into the complex relationships between daily-life walking patterns, morbidity, and falls.
引用
收藏
页码:2588 / 2594
页数:7
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