Healthcare data monitoring system

OData support
Supervisor:
Dr. Forstner Bertalan
Department of Automation and Applied Informatics

Nowadays, sensors have become cheaper, and more popular among users. The proliferation of wearable sensors helped accelerate this process as well, which caused the Quantified Self movement to gain popularity. People like to obtain quantified feedback from their daily life to improve their performance.

This process also affected the healthcare industry as there are a lot of sensors with services built on them. However, the low number of supported sensors, their quality and ability to cooperate with other systems led to limited proliferation.

In my thesis I present the design, and development of a software system, which can be easily expanded with different sensors as a result of its modular structure. By automatically analyzing the results of the performed measurements, users can receive immediate feedback, regarding their current health status.

Besides the collection of measurement data, correlation among them may be found, which helps us discovering relations between different diseases.

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