Context-aware physiological data acquisition and processing with wireless sensor networks

Wearable devices are a novel method for sensing physiological parameters of subjects. Even though some of them are equipped with multiple sensors, usually each parameter is analyzed separately. It often leads to false alarm generation and thus limited acceptability of these systems. We propose not only to combine multi-sensor data available on the wearable device, but also to interface the wearable nodes with a mesh network of sensing devices deployed in the environment. Such solution enables context-sensitive analysis of the physiological data leading to correct situation assessment and reliable alarm generation. The wireless sensor network provides reliable and low power communication medium for the wearable devices. We base our system on ECG and acceleration data acquired by the wearable nodes along with descriptive localization and environmental data from the wireless sensor network. We present the architecture of the proposed system and an example implementation both indoors and outdoors. The proposed system is easy to implement, flexible and scalable which makes it suitable for large area deployments.