Aggregator to connect in-body sensors to the health record system

Sammanfattning: Wireless connected Implanted Medical Devices are becoming more and more common. Also, the increasing connectivity of medical sensors opens room for improving one important field of Health Care, Remote Patients Monitoring. Therefore, to explore this scenario, thisthesis aims to create a device that works as an Aggregator of data arising from Implanted Medical Devices. This Aggregator will then transmit the data autonomously to a Health Care monitoring provider. The main objective of the Aggregator is to provide the technology for constant monitoring of the patients' Implanted Health Care Sensors. To do that, in this thesis, we developed a prototype of theAggregator using a general-purpose embedded platform. The objective is to test the functioning of the system by receiving data,processing, encrypt and send it through Bluetooth to a specialized remote monitoring Health Application Platform called IHAP by Intel®. This platform provides a standard commercial platform to connect the Aggregator to the Health Care Monitoring providers. In the case of this thesis, the Swedish company Alleato provides a server to which the data was forwarded. Once in the server, Alleato can decrypt the data and provide it to the medical specialist. A prototype was developed in a Raspberry PI so the software platform of the Aggregator could be certified. A series of performance tests were made to determine the main constraints of this project. The objective is to establish the grounds for the future development ofan Aggregator in a specialized embedded platform. Therefore, the main code parts of the Aggregator were tested and compared with aGeneral-Purpose Microcontroller, the ARM Cortex M0 STM32F072, and also with the SoC from Nordic Semiconductors, the nRF52840. The STM32 results gave a reference of performance on how the functions perform in General Purposes Microcontrollers. However, as expected, the Nordic nRF52840 showed to be the fastest platform for processing the Aggregator's functions. Therefore, it represents the best candidate for future projects with the platform developed inthis thesis.