利用惯性测量单元估算 STEADI 性能

Jasmine Y. Liang , Mingyue Zhang , Nicholas R. Lamoureux , Jeni Lansing , Li-Shan Chou , Gregory J. Welk
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引用次数: 0

摘要

导言在美国,跌倒是老年人意外伤害致死的主要原因,是一个重大的公共卫生问题。美国疾病预防控制中心开发的跌倒风险评估工具包 STEADI 已被证明可以预测未来的跌倒情况。然而,由于功能评估和病史调查问卷的截止分数存在分歧,STEADI 在准确评估方面存在问题。可穿戴传感器技术为评估个人在真实世界环境中的运动表现提供了一种实用且可量化的替代方法。惯性测量单元(IMU)的使用为加强跌倒风险筛查提供了相当大的潜力。目的 本研究的主要目的是测试由 IMU 测量的 STEADI 功能评估表现与人工测量结果的一致性。方法27名参与者(年龄:74.37 ± 7.21)进行了STEADI测试,包括四阶段平衡测试(4SBT)、定时上行测试(TUG)和30秒椅子站立测试(30sCS)。通过采用等效测试,测试了人类评定者与 IMU 测量结果之间的 STEADI 一致性,α = 0.05。结果评定者与 IMU 的测量结果之间,TUG 的差异为 -0.23 秒,30sCS 的差异为 0.37,相当于 TUG 和 30sCS 的差异分别在 4 % 和 8 % 以内。在 4SBT 过程中,单腿站立的差异为 0.59 秒;但是,计算出的等效区域更大(22.7%)。 结论这项研究证明了使用 IMU 传感器来增强基于 STEADI 的跌倒风险筛查方案的可行性。未来可能仍需进行改进,以便在更大范围的人群中进行更广泛的应用和有效的筛查实践。
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Estimation of STEADI performance using inertial measurement unit

Introduction

Falls present a significant public health concern in the United States as a primary cause of unintentional injury-related deaths among older adults. A fall risk assessment toolkit STEADI developed by the CDC has been shown to predict future falls. However, STEADI has issues with accurate evaluations due to the disagreement on cut-off scores in functional assessments and history-taking questionnaires. Wearable sensor technology offers a practical and quantifiable alternative for assessing an individual's movement performance in real-world environments. The use of Inertial Measurement Units (IMUs) offers considerable potential to enhance fall risk screening.

Purpose

The primary aim of this study is to test the agreement of STEADI functional assessment performance measured by the IMUs in comparison to human-based measurements.

Method

27 participants (Age: 74.37 ± 7.21) performed STEADI, including the Four-Stage Balance Test (4SBT), Timed Up & Go Test (TUG), 30-second Chair Stand (30sCS) with IMU placed at the fifth lumbar vertebra which is the proxy location of whole-body Center of Mass. By adopting an equivalent test, the STEADI agreement was tested between the human rater and IMU measurements, giving α = 0.05.

Result

Between the results from evaluators and IMU, the difference in TUG is -0.23 s, and the difference in 30sCS is 0.37, which is equivalent to within 4 % and 8 % for TUG and 30sCS, respectively. The difference in single-leg stance during the 4SBT is 0.59 s; however, the calculated equivalence zone is larger (22.7 %).

Conclusion

This study demonstrates the feasibility of using IMU sensors to enhance fall risk screening protocols based on the STEADI. Future refinement may still need to enable broader application and effective screening practices on a larger scale of the population.

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