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首页> 外文期刊>IEEE transactions on neural systems and rehabilitation engineering >Gait Velocity and Chair Sit-Stand-Sit Performance Improves Current Frailty-Status Identification
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Gait Velocity and Chair Sit-Stand-Sit Performance Improves Current Frailty-Status Identification

机译:步态速度和椅子坐立两用性能改善了当前的体弱状态识别

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摘要

Frailty is characterized by a loss of functionality and is expected to affect 9.9% of people aged 65 and over. Here, current frailty classification is compared with a collection of selected kinematic parameters. A total of 718 elderly subjects (319 males and 399 females; age: 75.4 ± 6.1 years), volunteered to participate in this study and were classified according to Fried's criteria. Both the 30-s chair stand test (CST) and the 3-m walking test were performed and a set of kinematic parameters were obtained from a single inertial unit. A decision tree analysis was used to: 1) identify the most relevant frailty-related parameters and 2) compare validity of this classification. We found that a selected set of parameters from the 30-s CST (i.e., range of movement, acceleration, and power) were better at identifying frailty status than both the actual outcome of the test (i.e., cycles' number) and the normally used criteria (i.e., gait speed). For the pre-frail status, AUC improves from 0.531 using the actual test outcome and 0.516 with gait speed to 0.938 with the kinematic parameters criteria. In practice, this could improve the presyndrome identification and perform the appropriate actions to postpone the progression into the frail status.
机译:身体虚弱的特征是功能丧失,预计将影响9.9%的65岁及以上人口。在这里,将当前的脆弱分类与所选运动学参数的集合进行比较。共有718位老年受试者(319位男性和399位女性;年龄:75.4±6.1岁)自愿参加了这项研究,并根据Fried的标准进行了分类。进行了30 s椅子站立测试(CST)和3 m步行测试,并从单个惯性单元获得了一组运动学参数。决策树分析用于:1)识别最相关的脆弱相关参数,以及2)比较此分类的有效性。我们发现,从30秒CST中选择的一组参数(即运动范围,加速度和功率)比实际的测试结果(即循环次数)和正常情况下更能识别脆弱状态。使用的标准(即步态速度)。对于虚弱前状态,AUC从使用实际测试结果的0.531和步态速度的0.516提高到运动学参数标准的0.938。在实践中,这可以改善综合征前的识别并执行适当的措施以推迟进展为体弱的状态。

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