Optimization of a clinical Pulse Wave Velocity estimation system based on innovative graphene pressure sensors

As the World Health Organization estimates, around 18 million of people die from Cardiovascular Diseases every year, making them the leading cause of mortality globally. Early CVD diagnosis and treatment can significantly minimize the risk of premature death and ensure patients a normal life. Among the several potential predictors, arterial stiffness has been shown to be a valuable indicator for assessing cardiovascular risk and is closely related to Pulse Wave Velocity (PWV). The term "Pulse Wave Velocity" refers to the rate at which the pressure wave within the arteries propagates, and it is typically assessed between the carotid and femoral sites. Nowadays, its estimation is executed using expensive technologies such as applanation tonometry and ultrasound, which constrain its usage in a clinical setting and increased over the last few years, the need for non-invasive, low-cost, clinical devices. For this reason, this thesis project aims to optimize an already designed, at the early experimental stage, clinical PWV estimation system. It is based on a Pyboard D-series and the sensitive elements involved in the transduction mechanism are innovative piezoresistive graphene-based pressure sensors, created in partnership with the Nanochemistry research group, at “Institut de Science et d’Ingénierie Supramolécularies” of the University of Strasburg. The first part of the thesis has been focused on the characterization of several newly fabricated sensors, with two different shapes: rectangular and circular. They are characterized by a high sensibility and a short time response, which make them a good solution for this application. However, the characterization was a fundamental step to identify and integrate the best functioning one in the system. Then, to consolidate the validation process the system has been tested in a clinical environment, thanks to the collaboration with “A.O.U. Città della Salute e della Scienza di Torino”. The results have been inconsistent, revealing a system able to acquire the signal but not giving the stability needed for the application. For these reasons the second part of the thesis work has been focused on developing a new system configuration to obtain electrical stability and reduce power consumption; the Pyboard D-series has been replaced with a STM32 Discovery kit, produced by STMicroelectronics. The conditioning circuit, based on a current controlled Wheatstone bridge, has been implemented on two different Printed Circuit boards (PCB). With the goal of reducing the possible noise, each of them has been designed with a specific shape to favour the close integration with the microcontroller board and the sensitive parts. Given the hardware, a specific firmware has been implemented enabling the acquisition and data transmission to the PC. Among the different aspects that the firmware manages, there is the interaction with the Graphical User Interface (GUI) whose primary purpose is the real-time display of the acquired signals. Finally, the newly configured system demonstrated its functioning as being capable of acquiring signals and transmitting them via USB to the PC. Compared with the previous, it shows electrical robustness and better performance representing a solid starting point for future optimizations.