|Title:||State-Of-The-Art on eHealth@home System Architectures|
|Subject:||Computer network engineering|
According to the statistics, by 2030, the percentage of elderly people will increase with 6.1%, compared to 2008 in the European union. We are also facing the problem of birth rates that are below the level needed for a sustained population. This results in a growing need for additional healthcare services and consequently more healthcare cost. In 2008, four persons of working age were supporting one person aged 65 or older, while projection shows that by 2030 the number of working persons will decrease to 2.5. This calls for less expensive solutions in healthcare that will utilize the benefits of modern technology, providing distance monitoring of elderly, and avoiding hospitalization when it is possible.
Technical advances in physiological sensing devices and wireless connectivity provided by the IoT can enable dramatic changes in the ways health monitoring and remote healthcare will be performed in the future. However, for such changes to take place, the enabling technologies must be employed with the well-being of the patient in focus, since neither individuals nor society would accept IoT solutions that mismatch the standards of current best practice in healthcare. IoT for health monitoring systems can enable new possibilities not available to patients today, especially to those not ill enough to be admitted to a hospital. By providing low-cost solutions to in-home monitoring, IoT can enable monitoring of such patients, enabling early detection of signs of deteriorating health, allowing for earlier responses and treatment. In order for in-home monitored patients to feel safe and secure when staying at their homes, the IoT solutions used must guarantee safety and security at a more technical level. Hence, one important focus of this overview is the security of the health monitoring systems studied.
Additionally, emerging network technologies, including the next generation mobile technology (5G), will form the backbone of future healthcare. 5G is a key enabling technology for the IoT, smart pharmaceuticals, and individualized medicine. The features of 5G, such as low latency, reliability, performance, and flexibility, enable novel features to a better quality of eHealth services.
There are several use cases defined in the remote health monitoring of patients and elderly people. This Thesis research concentrates on the literature review on current system architectures for health monitoring applications at home by considering their requirements and challenges. As an example, it is mandatory to concentrate on the close loop medication management (CLMM) that provides a flexible and adjustable dosing through a closed loop feedback system, which is very useful for ADHD patients. The research should include the related works in terms of current products in the market together with academic research in this area.
To enable use cases such as CLMM for the eHealth@home, various types of radio hardware and wireless technologies can be employed. It is important to discuss on the heterogeneity of such system infrastructure and elaborate the existing system designs for collecting measurements over wireless links. This Thesis will also require discussing on different data collection and data processing strategies by addressing algorithms employed for data aggregation and data storage using Fog and Cloud computing paradigm.
There are several eHealth@home monitoring architectures in the literature. This thesis elaborates the most recent system architectures by comparing them in terms of their wireless communication technologies, data collection and data storage strategies with a special focus on the CLMM use case. It is important to discuss on all the required components for designing and developing an eHealth@home use case considering the current low-power wireless networks and 5G technologies.
The main outcome of this Thesis is a qualitative comparison of various eHealth@home system architectures with special focus on the requirements and challenges for developing a CLMM use case.
|IDT supervisors:||Hossein Fotouhi, Maryam Vahabi|
|Company contact:||Alten Sverige AB Detlef Scholle firstname.lastname@example.org|