Context-aware QoS provisioning for an M-health service platform

Inevitably, healthcare goes mobile. Recently developed mobile healthcare (i.e., m-health) services allow healthcare professionals to monitor mobile patient's vital signs and provide feedback to this patient anywhere at any time. Due to the nature of current supporting mobile service platforms, m-health services are delivered with a best-effort, i.e., there are no guarantees on the delivered Quality of Service (QoS). In this paper, we argue that the use of context information in an m-health service platform improves the delivered QoS. We give a first attempt to merge context information with a QoS-aware mobile service platform in the m-health services domain. We illustrate this with an epilepsy tele-monitoring scenario

Context-aware, ontology-based, service discovery

Service discovery is a process of locating, or discovering, one or more documents, that describe a particular service. Most of the current service discovery approaches perform syntactic matching, that is, they retrieve services descriptions that contain particular keywords from the user’s query. This often leads to poor discovery results, because the keywords in the query can be semantically similar but syntactically different, or syntactically similar but semantically different from the terms in a service description. Another drawback of the existing service discovery mechanisms is that the query-service matching score is calculated taking into account only the keywords from the user’s query and the terms in the service descriptions. Thus, regardless of the context of the service user and the context of the services providers, the same list of results is returned in response to a particular query. This paper presents a novel approach for service discovery that uses ontologies to capture the semantics of the user’s query, of the services and of the contextual information that is considered relevant in the matching process

A Framework for Smart Distribution of Bio-signal Processing Units in M-Health

This paper introduces the Bio-Signal Processing Unit (BSPU) as a functional component that hosts (part of ) the bio-signal information processing algorithms that are needed for an m-health application. With our approach, the BSPUs can be dynamically assigned to available nodes between the bio-signal source and the application to optimize the use of computation and communication resources. The main contributions of this paper are: (1) it presents the supporting architecture (e.g. components and interfaces) and the mechanism (sequence of interactions) for BSPU distribution; (2) it proposes a coordination mechanism to ensure the correctness of the BSPU distribution; (3) it elaborates the design of smooth transition during BSPU distribution in order to minimize the disturbance to the m-health streaming application

Towards an application framework for context-aware m-health applications

Several social issues, like aging, stimulate the use of mobile ICT applications for mobile healthcare (e.g., telemonitoring). To support novel m-health applications, the consequences of developing these applications should be considered in the scope of a comprehensive architecture. This paper describes ongoing research that focuses on developing an application framework for supporting the development of context-aware m-health applications. It gives initial requirements for such a framework and it gives a first attempt for a functional decomposition. The use of the framework is illustrated by means of an epilepsy tele-monitoring scenario

Context Management and Semantic Modelling for Ambient Intelligence

Ambient Intelligence aims at pushing forward a user centric vision of Pervasive Computing, where the environment better serves our need. This paper describes our current work on modelling and managing context information for smart environments

Enhancing guideline-based decision support with distributed computation through local mobile application

We introduce the need for a distributed guideline-based decision support (DSS) process, describe its characteristics, and explain how we implemented this process within the European Union’s MobiGuide project. In particular, we have developed a mechanism of sequential, piecemeal projection, i.e., 'downloading' small portions of the guideline from the central DSS server, to the local DSS in the patient's mobile device, which then applies that portion, using the mobile device's local resources. The mobile device sends a callback to the central DSS when it encounters a triggering pattern predefined in the projected module, which leads to an appropriate predefined action by the central DSS, including sending a new projected module, or directly controlling the rest of the workflow. We suggest that such a distributed architecture that explicitly defines a dialog between a central DSS server and a local DSS module, better balances the computational load and exploits the relative advantages of the central server and of the local mobile device

Patient-oriented computerized clinical guidelines for mobile decision support in gestational diabetes

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients’ self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient’s access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients’ personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients’ acceptance of the whole system

Change Request Risk Model: Improving The Migration Of Networks

Internet and mobile phones have become essential in our lives. Without the internet and our smart phones, large parts of our society would stop functioning or even collapse completely. It is therefore of critical importance that the service is of the highest quality and that the delivery of service is not interrupted. Telecommunication providers are responsible for exploiting and maintaining the infrastructure necessary for delivering mobile and internet connections. It is not an easy market to survive in. Competition is fierce and the clientele demands constant service of the highest quality. This is a big challenge for telecommunication providers. In order to be able to deliver the best quality, maintenance is necessary. But maintenance is often the cause of service interruption. Combined with the fact that technology is evolving at such a pace that upgrades are coming faster and faster, the demand for maintenance has never been higher. Efficiently organising these maintenance activities has therefore become a priority.Engineering and Policy Analysi

Graduation Committee: University of Twente:

The internet is evolving from a data repository to a more complex service provisioning system. Besides the upcoming of enabling technologies for internet service provisioning like web services, also business to business integration can be seen as a driving force for this evolution. Therefore, a growing amount of electronic services is deployed on the internet. Before services can be used, they first have to be found. Service discovery is a mechanism for finding services. Current mechanisms are syntactic methods (i.e. they match service requests and descriptions of service offerings based on keywords) which often lead to a poor quality result. This thesis focuses on how the quality of the service discovery result can be improved. Service discovery quality denotes the extent to which a returned match is relevant for the user. This thesis consists of two parts. In the first part, a problem analysis on service discovery is presented. The second part uses knowledge from the problem analysis to create a new service discovery approach. Key aspects of this new approach are context-awareness, ontologies and semantic reasoning. Finally, this new approach is implemented in a prototype to be able t