论文标题
使用多元环境环境时间序列数据预测与痴呆相关的搅动
Prediction of Dementia-related Agitation Using Multivariate Ambient Environmental Time-series Data
论文作者
论文摘要
与痴呆相关的搅动会导致痴呆症护理人员（CG）和痴呆症患者（PWD）引起高压力。当前的临床研究表明，痴呆症的躁动可能会受到环境环境和其他上下文因素的影响或触发。在这项研究中，我们通过分析使用PWD及其CG家中的遥感系统收集的环境环境数据来评估这一假设。此外，我们确定是否可以从环境环境数据中预测与痴呆相关的搅动的发生，从而通过环境改变可以预防搅拌。这些收集的数据用于使用预测模型方法来学习环境模式。在模型训练中使用的搅拌标签由CGS与PWD一起提供。搅动预测模型评估的结果表明，环境环境可以用作即将进行痴呆相关搅动的预测因子。我们还观察到搅动的环境触发器是PWD特异的。还讨论了用于理解痴呆症激动触发因素的未来机会和技术。
Dementia-related agitation causes high stress for dementia caregivers (CG) and to persons with dementia (PWD). Current clinical research suggests that dementia agitation can be affected or triggered by the ambient environment and other contextual factors. In this study, we evaluate this hypothesis through an analysis of ambient environmental data collected with a remote sensing system deployed in the homes of PWDs and their CGs. Furthermore, we determine if the occurrence of dementia-related agitation can be predicted from ambient environmental data, creating the potential for agitation to be prevented via the environmental alteration. These collected data are used to learn the environmental patterns using a predictive model approach. The agitation labels, used in model training, are provided by the CGs living with the PWDs. The results of the agitation prediction model evaluation suggest that ambient environment can be used as predictors for upcoming dementia-related agitation. We also observed that environmental triggers for agitation are PWD-specific. Future opportunities and techniques used to understand triggers for dementia agitation are also discussed.
