Activity and Context Recognition with Wireless Body Area Networks

Wireless Body Area Networks (WBAN) consist of wearable or body-embedded wireless sensors which may be used to collect information about the movement of the body or the vital signals of the person. Besides the sensors, WBANs have a gateway node, such as a smart phone, that enables communication between the WBAN and the external networks. Due to the information they provide and their unobstrusiveness, WBANs may be used for a wide range of applications. In this project, we aim to develop a WBAN based activity recognition system especially for the elderly. The system will monitor the vital and movements signals as well as the location of the person via RFID or GPS, since these will have significant information about the activity the person is engaged in. Constant monitoring of body motion and vital signals will enable us to detect emergencies such as falls, just as high level activity recognition will provide a context for the long-term health monitoring application, which will be the focus of this project. Performance analysis for the proposed system will be carried out via a test application on actual sensor nodes. The next step, which is also one of the main goals of the project, will be to gather data from actual elderly or chronically ill people and test the system on this data set.

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