A Case-Driven Ambient Intelligence System for Elderly in-Home Assistance Applications
A Case-Driven Ambient Intelligence System for Elderly in-Home Assistance Applications
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DOI：
10.1109/tsmcc.2010.2052456
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发表时间：
2011-03
期刊：
影响因子：
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通讯作者：
Feng Zhou;R. Jiao;Songlin Chen;Daqing Zhang
中科院分区：
文献类型：
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作者：
Feng Zhou;R. Jiao;Songlin Chen;Daqing Zhang
老年人家庭援助（EHA）传统上由人类护理人员负责，为老年人的日常生活提供家庭护理援助。新兴的环境智能 (AmI) 技术表明其在 EHA 应用中具有巨大潜力，因为它可以有效地构建对人类存在敏感且响应的情境感知环境。本文提出了一种案例驱动的 AmI (C-AmI) 系统，旨在感知、预测、推理并采取行动以应对老年人在家中的日常生活活动 (ADL)。 C-AmI 系统架构是通过在一个连贯的框架内综合各种传感器、活动识别、基于案例的推理以及 EHA 定制知识而开发的。 EHA 信息模型是通过活动识别、案例理解和辅助动作层制定的。粗糙集理论应用于基于智能家居中嵌入的传感器平台的 ADL 建模。辅助动作参考先验案例解决方案完成，并通过人-物-环境交互在AmI系统内实施。初步研究结果表明 C-AmI 在增强 EHA 应用的情境意识方面具有潜力。
Elderly in-home assistance (EHA) has traditionally been tackled by human caregivers to equip the elderly with homecare assistance in their daily living. The emerging ambience intelligence (AmI) technology suggests itself to be of great potential for EHA applications, owing to its effectiveness in building a context-aware environment that is sensitive and responsive to the presence of humans. This paper presents a case-driven AmI (C-AmI) system, aiming to sense, predict, reason, and act in response to the elderly activities of daily living (ADLs) at home. The C-AmI system architecture is developed by synthesizing various sensors, activity recognition, case-based reasoning, along with EHA-customized knowledge, within a coherent framework. An EHA information model is formulated through the activity recognition, case comprehension, and assistive action layers. The rough set theory is applied to model ADLs based on the sensor platform embedded in a smart home. Assistive actions are fulfilled with reference to a priori case solutions and implemented within the AmI system through human-object-environment interactions. Initial findings indicate the potential of C-AmI for enhancing context awareness of EHA applications.