Sahlab Nada, Jazdi Nasser
University of Stuttgart.
Stud Health Technol Inform. 2020 Sep 4;273:163-169. doi: 10.3233/SHTI200633.
The demographic change is no longer a prognosis, but a reality seen in everyday life situations and requires mechanisms to make the public and private space elderly-adequate. These required mechanisms need to consider the varying aging process for each individual as well as adapt to the dynamic daily life of individuals characterized by spatial, temporal and activity variance. Developing assistance systems that are user-adaptive within dynamic environments is a challenging task. AI-based cyber-physical assistance systems enable such adaptive, flexible and individual assistance by processing acquired data from the physical environment using cyber resources and delivering intelligent assistance as well as interfaces to further medical services. This contribution discusses a flexible, reusable, and user-specific concept for AI-based assistance systems. Relying on distributed and heterogeneous data, the user's context is continuously modeled and reasoned over to infer actionable knowledge within a middleware between the data layer and the application layer. To demonstrate the applicability of the concept, the use case of intelligently supporting patients' medication adherence is shown.
人口结构变化已不再是一种预测，而是在日常生活中可见的现实，这就需要建立一些机制，使公共和私人空间都适合老年人使用。这些所需的机制需要考虑到每个人不同的衰老过程，同时也要适应个体动态的日常生活，其特点是在空间、时间和活动方面存在差异。开发在动态环境中具有用户适应性的辅助系统是一项具有挑战性的任务。基于人工智能的网络物理辅助系统通过利用网络资源处理从物理环境中获取的数据，并提供智能辅助以及与进一步医疗服务的接口，从而实现这种适应性强、灵活且个性化的辅助。本文探讨了一种基于人工智能的辅助系统的灵活、可重复使用且针对用户的概念。依靠分布式和异构数据，在数据层和应用层之间的中间件中，不断对用户的上下文进行建模和推理，以推断出可采取行动的知识。为了证明该概念的适用性，展示了智能支持患者药物依从性的用例。
