The concept of Cyber-Medicine System (CMS) is applied to research and development of medical information systems where the Internet is used to integrate medical devices and healthcare services into the system and to connect patients and medical professionals. In this paper, the authors generalize the concept to Socio-CMS, where the social world is added to the fusion of physical and cyber worlds. The social world affects the end-user activity and provides opportunities for collaborative work. A semantic layer is introduced to integrate all system and domain objects from the three digitalized worlds into a smart space: multi-source data, ongoing processes, situation attributes, reasoning rules, and human activity. All objects are dynamically related, leading to such a knowledge-rich structure as a semantic network. Data mining and analytics apply semantic algorithms for this network, including the Big Data case. The derived knowledge feeds construction of advanced healthcare services for supporting medical professionals and for assisting patients.
The article studies the smart spaces approach applied for development of mobile healthcare (m-Health) services deploying in Internet of Things (IoT) environments. The authors consider a reference architecture model of the service ecosystem with focus on intelligent utilization of multi-source data originated from the IoT environment. Based on the architecture the authors introduce two reference scenarios: assistance in providing the first aid and communication with the hospital information system. For the architectural model and the scenarios pilot implementations are developed on the open source Smart-M3 platform.
Forward-looking personalized health care services tend to utilize benefits of smart spaces. Particularly, a smartphone app can be used as a hub for collecting and preprocessing of the vital health parameters provided by various sensors. Thus, the IoT-enabled mHealth apps should be designed to be easy extendable for the new kinds of data sources and processing units. In this paper, the architecture of mobile app supporting several data sources is described. Also, implementation issues related to Android and Windows Phone platforms are discussed.
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