Abstract-Wireless sensor networks are going to allow for ubiquitous health monitoring, improving users' well-being, the healthcare system, and helping to quickly react on emergency situations. Meeting the strict security needs of these ubiquitous medical applications is a big challenge, since safety and privacy of medical data has to be guaranteed all the way from the sensor nodes to the back-end services, the system has to fulfill latency needs, and lots of mobility is expected.In this paper, we introduce a deployment model for wireless sensor networks for pervasive health care based on the concepts of patient area networks and medical sensor networks, and propose a complete and efficient security framework for them. Our security framework is organized into three layers, addressing the operational requirements and security needs at the patient area network, medical sensor network and back-end levels. We specify how these layers are interconnected with each other as well as the needed security mechanisms that allow for the efficient and practical deployment of secure pervasive health care systems based on wireless sensor networks.
We present a novel mechanism intended to provide Quality of Service (QoS) for IEEE 802.15.4-based Wireless Body Sensor Networks (WBSN) used for pervasive healthcare applications. The mechanism was implemented and validated on the AquisGrain WBSN platform. Our results show that the QoS performance of the IEEE 802.15.4 standard can be considerably improved in terms of reliability and timeliness for intra-node as well as inter-node scenarios while keeping backward compatibility to ensure interoperability.
This paper describes an unobtrusive IEEE 802.15.4-based wireless Body Sensor Network (BSN) that enables continuous cuff-less blood pressure monitoring, opening up new perspectives for hypertension diagnosis and treatment, cardio-vascular event detection, and stress monitoring. We estimate the arterial blood pressure based on the Pulse Arrival Time (PAT), which is measured with a waist electrocardiogram (ECG) and an ear photo-plethysmogram (PPG). The PAT measurement requires the synchronization of the wireless sensors' clocks. This is achieved with the Flooding Time Synchronization Protocol (FTSP). The evaluation of both the implemented time synchronization and the robustness of the wireless data transmission yielded promising results. Future work will include the study of packet collisions in synchronized IEEE 802.15.4 networks, the enhancement of the BSN with additional context-providing sensors (e.g. accelerometer, magnetometer, thermistor), and the integration of the blood pressure estimation algorithm in a wireless sensor unit.
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