LoCa: A Location & Context-aware eHealth Infrastructure (Finished)

If we consider our aging society, the amount of elderly people suffering from one or more chronic diseases is increasing. Telemonitoring applications in home care enable healthcare institutions to take care of their patients while they are out of hospital. This is especially useful for managing various chronic diseases as well as for measuring the effects of treatments under real-life conditions.
Given appropriate sensor technology and a reliable infrastructure for telemonitoring and data stream processing, i.e., an infrastructure their users can count on, caregivers will decide to equip their patients with a wearable telemonitoring system consisting of, e.g., ECG, blood pressure, and oxygen saturation sensors attached to patient’s body. Context information about the patient like his current activity or position, and body sensor information is processed by a telemonitoring infrastructure. It will analyze the data accumulated, extract and forward relevant information to the care provider in charge. In this scenario, disease management is improved by detecting critical situations that might occur between consultations of the physician. In case of relevant changes of the patient’s health condition, his/her physician in charge or the emergency service will be automatically informed, and is able to retrieve all medical important data.
Similar technologies are also needed for applications in stationary care. Consider, for instance, a doctor on a ward round who is equipped with a PDA for accessing the electronic health record of a patient she is about to see. Due to the display limitations of these devices, it would be desirable to dynamically switch to a more powerful display (e.g., monitor in the examination room) whenever this is needed, for instance for the display of high-resolution X-Ray images. Another important aspect is the adaptation to different end users. The electronic health record could provide a special interface for doctors and another one for nurses. Using this interface adaptation makes it easier and faster for a nurse and a doctor to fill in and access the needed information.
Such applications require an infrastructure that is able to dynamically adapt to the particular context and location of a user. This includes the handling of interfaces (sessions that need to be transferred from one device to another) but also the location and context-dependent combination, processing, and managing of data, in particular of continuous data streams coming from the different soft- and hardware sensors over heterogeneous devices like body sensors integrated in embedded systems, mobile devices, like PDAs or smart phones, which allow for patient mobility, and stationary PCs for further processing and long term storage connected. This location and context-aware adaptation must be done in a user-friendly way and has to be done on top of a highly dependent and reliable infrastructure which can potentially be life-saving.
From an application point of view, the project jointly addresses the automatic adaptation of applications in the two fields identified above, namely home care and stationary care. From a technical point of view, the project will jointly apply advanced mechanisms for dynamic, context and location-dependent adaptation to two areas, namely i.) user interface generation and services and ii.) generation of process-based distributed applications.
The project emphasizes on application-oriented requirements in the healthcare domain. Moreover, the project aims at integrating and building on top of existing research results from both partners. In contrast to related work in the field which mostly investigated on very specific technical issues in the context of eHealth applications, this project aims at a holistic approach to context- and location-awareness in healthcare applications. In particular, the project will develop an integrated software prototype system in order to evaluate and proof the fulfillment of the required issues.

Start / End Dates

01.11.2008 - 31.10.2011

Partners

Prof. Dr. Andreas Meier, University Fribourg

Funding Agencies

Hasler Foundation

Staff

Research Topics

Publications

2014
2012
2011
2010
2009