Ayena Johannes C, Zaibi Helmi, Otis Martin J-D, Menelas Bob-Antoine J
IEEE Trans Neural Syst Rehabil Eng. 2016 Dec;24(12):1351-1362. doi: 10.1109/TNSRE.2015.2508960. Epub 2015 Dec 17.
The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.
本研究的目的是通过计算日常活动中的实时跌倒风险,改进并简化用于评估老年人在家中跌倒风险的方法。为了提高跌倒风险的实时计算能力,提出了一种闭环平衡模型,并将其与单腿站立测试(OLST)进行比较。该平衡模型允许研究受到不可预测扰动的人的姿势反应。29名志愿者参与了本研究,以评估所提出系统的有效性,其中包括17名老年参与者:10名健康老年人(68.4±5.5岁)、7名帕金森病(PD)患者(66.28±8.9岁)和12名健康年轻人(28.27±3.74岁)。我们的研究表明,基于位于仪器化鞋垫内的四个低成本力传感器进行压力中心测量,OLST评分与跌倒风险之间存在关联,这可以使用我们建议的闭环平衡模型进行预测。对于在家中的长期监测,该系统可以纳入医疗电子记录,并且作为诊断辅助工具可能会很有用。