Eight-Week Remote Monitoring Using a Freely Worn Device Reveals Unstable Gait Patterns in Older Fallers
Eight-Week Remote Monitoring Using a Freely Worn Device Reveals Unstable Gait Patterns in Older Fallers
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DOI：
10.1109/tbme.2015.2433935
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发表时间：
2015-11-01
影响因子：
4.6
通讯作者：
Delbaere, Kim
中科院分区：
文献类型：
--
作者：
Brodie, Matthew A.;Lord, Stephen R.;Delbaere, Kim
目的：开发算法，在长期监测期间使用自由佩戴设备的数据远程检测步态障碍。识别描述步态表现如何在几周内分布的统计模型。确定可靠评估跌倒倾向增加所需的数据窗口。研究方法：1085天的步行数据收集从18个独立生活的老年人（平均年龄83岁）使用自由佩戴的吊坠传感器（外壳三轴加速度计和压力传感器）。从几个加速度计衍生的步态特征（包括数量，曝光，强度和质量）的统计分布进行了比较，有和没有跌倒的历史。结果：参与者完成了更多的短距离行走相对于长距离行走，近似于幂律。少于13.1 s的步行占步行相关福尔斯的50%。日常生活节奏是双峰和步时间变异遵循对数正态分布。跌倒者每次行走的步数明显较少，并且相对更多地暴露于短距离行走和更短的步时变异模式。结论：使用自由佩戴的设备和基于小波的分析工具，可以长期监测大于或等于三步的行走。在老年人中，短距离步行构成了福尔斯暴露的很大比例。为了识别下降者，变异模态可能是比变异均值更好的集中趋势度量。一周的监测足以可靠地评估长期跌倒倾向。重要性：步态表现的统计分布为未来可穿戴设备的开发和日常生活行走模式、发病率和福尔斯之间复杂关系的研究提供了参考。
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.