A Service-oriented Architecture for Ambient-Assisted Living

Ambient-Assisted Living (AAL) is currently an important research and development area, mainly due to the rapidly aging society, the increasing cost of health care, and the growing importance that individuals place on living independently. The general goal of AAL solutions is to apply ambient-assisted intelligence to enable people with specific demands (e.g. handicapped or elderly) to live in their preferred environment longer by tools (i.e. smart objects, mobile and wearable sensors, intelligent devices) being sensitive and responsive to the presence of people and their actions. The research describes the design and development of a novel service-oriented system architecture where different smart objects and sensors are combined to offer ambient-assisted living intelligence to older people. The design stage is driven by a user-centred approach to define an interoperable architecture and human-oriented principles to create usable products and well-accepted services. Such architecture has been realized in the context of an Italian research project funded by the Marche Region and promoted by INRCA (National Institute on Health and Science of Aging) in the framework of smart home for active ageing and ambient assisted living. The result is an interoperable and flexible platform that allows creating user-centred services for independent living

An Integrated Framework to Achieve Interoperability in Person-Centric Health Management

The need for high-quality out-of-hospital healthcare is a known socioeconomic problem. Exploiting ICT's evolution, ad-hoc telemedicine solutions have been proposed in the past. Integrating such ad-hoc solutions in order to cost-effectively support the entire healthcare cycle is still a research challenge. In order to handle the heterogeneity of relevant information and to overcome the fragmentation of out-of-hospital instrumentation in person-centric healthcare systems, a shared and open source interoperability component can be adopted, which is ontology driven and based on the semantic web data model. The feasibility and the advantages of the proposed approach are demonstrated by presenting the use case of real-time monitoring of patients' health and their environmental context

Big data architecture for pervasive healthcare: a literature review

Pervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture

A new framework architecture for next generation e-Health services

The challenge for fast and low-cost deployment of ubiquitous personalized e-Health services has prompted us to propose a new framework architecture for such services. We have studied the operational features and the environment of e-Health services and we led to a framework structure that extends the ETSI/Parlay architecture, which is used for the deployment of standardized services over the next generation IP networks. We expanded the ETSI/Parlay architecture with new service capability features as well as sensor, profiling and security mechanisms. The proposed framework assists the seamless integration, within the e-Health service structure, of diverse facilities provided by both the underlying communication and computing infrastructure as well as the patient's bio and context sensor networks. Finally, we demonstrate the deployment of a tele-monitoring service in smart home environment based on the proposed framework architecture

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

An ontology-driven architecture for data integration and management in home-based telemonitoring scenarios

The shift from traditional medical care to the use of new technology and engineering innovations is nowadays an interesting and growing research area mainly motivated by a growing population with chronic conditions and disabilities. By means of information and communications technologies (ICTs), telemedicine systems offer a good solution for providing medical care at a distance to any person in any place at any time. Although significant contributions have been made in this field in recent decades, telemedicine and in e-health scenarios in general still pose numerous challenges that need to be addressed by researchers in order to take maximum advantage of the benefits that these systems provide and to support their long-term implementation. The goal of this research thesis is to make contributions in the field of home-based telemonitoring scenarios. By periodically collecting patients' clinical data and transferring them to physicians located in remote sites, patient health status supervision and feedback provision is possible. This type of telemedicine system guarantees patient supervision while reducing costs (enabling more autonomous patient care and avoiding hospital over flows). Furthermore, patients' quality of life and empowerment are improved. Specifically, this research investigates how a new architecture based on ontologies can be successfully used to address the main challenges presented in home-based telemonitoring scenarios. The challenges include data integration, personalized care, multi-chronic conditions, clinical and technical management. These are the principal issues presented and discussed in this thesis. The proposed new ontology-based architecture takes into account both practical and conceptual integration issues and the transference of data between the end points of the telemonitoring scenario (i.e, communication and message exchange). The architecture includes two layers: 1) a conceptual layer and 2) a data and communication layer. On the one hand, the conceptual layer based on ontologies is proposed to unify the management procedure and integrate incoming data from all the sources involved in the telemonitoring process. On the other hand, the data and communication layer based on web service technologies is proposed to provide practical back-up to the use of the ontology, to provide a real implementation of the tasks it describes and thus to provide a means of exchanging data. This architecture takes advantage of the combination of ontologies, rules, web services and the autonomic computing paradigm. All are well-known technologies and popular solutions applied in the semantic web domain and network management field. A review of these technologies and related works that have made use of them is presented in this thesis in order to understand how they can be combined successfully to provide a solution for telemonitoring scenarios. The design and development of the ontology used in the conceptual layer led to the study of the autonomic computing paradigm and its combination with ontologies. In addition, the OWL (Ontology Web Language) language was studied and selected to express the required knowledge in the ontology while the SPARQL language was examined for its effective use in defining rules. As an outcome of these research tasks, the HOTMES (Home Ontology for Integrated Management in Telemonitoring Scenarios) ontology, presented in this thesis, was developed. The combination of the HOTMES ontology with SPARQL rules to provide a flexible solution for personalising management tasks and adapting the methodology for different management purposes is also discussed. The use of Web Services (WSs) was investigated to support the exchange of information defined in the conceptual layer of the architecture. A generic ontology based solution was designed to integrate data and management procedures in the data and communication layer of the architecture. This is an innovative REST-inspired architecture that allows information contained in an ontology to be exchanged in a generic manner. This layer structure and its communication method provide the approach with scalability and re-usability features. The application of the HOTMES-based architecture has been studied for clinical purposes following three simple methodological stages described in this thesis. Data and management integration for context-aware and personalized monitoring services for patients with chronic conditions in the telemonitoring scenario are thus addressed. In particular, the extension of the HOTMES ontology defines a patient profile. These profiles in combination with individual rules provide clinical guidelines aiming to monitor and evaluate the evolution of the patient's health status evolution. This research implied a multi-disciplinary collaboration where clinicians had an essential role both in the ontology definition and in the validation of the proposed approach. Patient profiles were defined for 16 types of different diseases. Finally, two solutions were explored and compared in this thesis to address the remote technical management of all devices that comprise the telemonitoring scenario. The first solution was based on the HOTMES ontology-based architecture. The second solution was based on the most popular TCP/IP management architecture, SNMP (Simple Network Management Protocol). As a general conclusion, it has been demonstrated that the combination of ontologies, rules, WSs and the autonomic computing paradigm takes advantage of the main benefits that these technologies can offer in terms of knowledge representation, work flow organization, data transference, personalization of services and self-management capabilities. It has been proven that ontologies can be successfully used to provide clear descriptions of managed data (both clinical and technical) and ways of managing such information. This represents a further step towards the possibility of establishing more effective home-based telemonitoring systems and thus improving the remote care of patients with chronic diseases

Data Modeling for Ambient Home Care Systems

Ambient assisted living (AAL) services are usually designed to work on the assumption that real-time context information about the user and his environment is available. Systems handling acquisition and context inference need to use a versatile data model, expressive and scalable enough to handle complex context and heterogeneous data sources. In this paper, we describe an ontology to be used in a system providing AAL services. The ontology reuses previous ontologies and models the partners in the value chain and their service offering. With our proposal, we aim at having an effective AAL data model, easily adaptable to specific domain needs and services