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Validation of noninvasive body sensor network technology in the detection of agitation in dementia

机译:无创人体传感器网络技术在痴呆症躁动检测中的验证

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Objective: Agitated behaviors are one of the most frequent reasons that patients with dementia are placed in long-term care settings. This study aims to validate the ability of a custom Body Sensor Network (BSN) to capture the presence of agitation against currently accepted subjective measures, the Cohen-Mansfield Agitation Inventory (CMAI) and the Aggressive Behavior Scale (ABS) and to discriminate between agitation and cognitive decline. Methods: Six patients identified as being at high risk for agitated behaviors were enrolled in this study. The devices were applied at three sites for three hours while behaviors were annotated simultaneously and subsequently repeated twice for each enrolled subject. Results: We found that the BSN was a valid measure of agitation based on construct validity testing and secondary validation using non-parametric ANOVAs. Discussion: The BSN shows promise from these pilot results. Further testing with a larger sample is needed to replicate these results.
机译:目的:躁动的行为是痴呆症患者长期护理的最常见原因之一。这项研究旨在验证自定义人体传感器网络(BSN)针对当前公认的主观指标,Cohen-Mansfield激动量表(CMAI)和攻击行为量表(ABS)捕获躁动的能力以及区分躁动的能力和认知能力下降。方法:本研究招募了6名被确定为躁动行为高风险患者。该设备在三个地点使用了三个小时,同时对行为进行了注释,随后对每个入组受试者重复两次。结果:我们发现BSN是基于结构有效性测试和使用非参数方差分析进行二次验证的有效搅拌方法。讨论:BSN显示了这些试验结果的希望。需要使用更大的样本进行进一步测试以复制这些结果。

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