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Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review

机译:基于传感器的秋季风险评估,有或没有认知障碍的成年人:系统审查

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BACKGROUND:Higher age and cognitive impairment are associated with a higher risk of falling. Wearable sensor technology may be useful in objectively assessing motor fall risk factors to improve physical exercise interventions for fall prevention. This systematic review aims at providing an updated overview of the current research on wearable sensors for fall risk assessment in older adults with or without cognitive impairment. Therefore, we addressed two specific research questions: 1) Can wearable sensors provide accurate data on motor performance that may be used to assess risk of falling, e.g., by distinguishing between faller and non-faller in a sample of older adults with or without cognitive impairment?; and 2) Which practical recommendations can be given for the application of sensor-based fall risk assessment in individuals with CI? A systematic literature search (July 2019, update July 2020) was conducted using PubMed, Scopus and Web of Science databases. Community-based studies or studies conducted in a geriatric setting that examine fall risk factors in older adults (aged ≥60?years) with or without cognitive impairment were included. Predefined inclusion criteria yielded 16 cross-sectional, 10 prospective and 2 studies with a mixed design.RESULTS:Overall, sensor-based data was mainly collected during walking tests in a lab setting. The main sensor location was the lower back to provide wearing comfort and avoid disturbance of participants. The most accurate fall risk classification model included data from sit-to-walk and walk-to-sit transitions collected over three days of daily life (mean accuracy?=?88.0%). Nine out of 28 included studies revealed information about sensor use in older adults with possible cognitive impairment, but classification models performed slightly worse than those for older adults without cognitive impairment (mean accuracy?=?79.0%).CONCLUSION:Fall risk assessment using wearable sensors is feasible in older adults regardless of their cognitive status. Accuracy may vary depending on sensor location, sensor attachment and type of assessment chosen for the recording of sensor data. More research on the use of sensors for objective fall risk assessment in older adults is needed, particularly in older adults with cognitive impairment.TRIAL REGISTRATION:This systematic review is registered in PROSPERO ( CRD42020171118 ).? 2021. The Author(s).
机译:背景:更高的年龄和认知障碍与较高的堕落风险有关。可穿戴传感器技术可用于客观地评估电机落下危险因素,以改善防止实际运动干预措施。该系统审查旨在提供目前关于可穿戴传感器研究的最新概述,用于较老年成年人的秋季风险评估,有或没有认知障碍。因此,我们解决了两个具体的研究问题:1)可以穿戴传感器可以提供关于可用于评估跌倒风险的电机性能的准确数据,例如,通过区分衰落和非衰落的衰落和非衰落的较大的成人样本,或没有认知障碍? 2)可以在用CI的个体中应用基于传感器的秋季风险评估的哪种实用建议?系统文献搜索(2019年7月,2019年7月2020年7月)是使用PubMed,Scopus和Science数据库网进行的。在一个老年人的成瘾中进行的基于社区的研究或研究,其中包括有或没有认知障碍的老年人(年龄≥60岁)的秋季危险因素。预定义的纳入标准产生了16个横截面,10个前瞻性和2项,具有混合设计。结果:总体而言,在实验室设置中的步行测试期间主要收集基于传感器的数据。主要传感器位置是腰部,提供佩戴舒适度,避免参与者的干扰。最准确的秋季风险分类模型包括从日常生活的三天内收集的坐足和步行过渡的数据(平均准确性?=?88.0%)。 28分中的九分之一揭示了有关具有可能认知障碍的老年人传感器使用的传感器的信息,但分类模型比没有认知障碍的老年人的分类模型略微差(平均准确性?=?79.0%)。结论:使用可穿戴的秋季风险评估无论其认知状态如何,传感器都在老年人中是可行的。精度可以根据传感器位置,传感器附件和选择用于记录传感器数据的评估类型而变化。需要更多关于使用传感器对老年人的客观坠落风险评估的研究,特别是在具有认知障碍的老年人中.Tiral注册:该系统审查在Prospero(CRD42020171118)注册。? 2021.作者。

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