WDSS-RP3: Multi-parameter Sensing Platform for Proactive Hypertension Diagnostics Using Artificial Intelligence

Principal Investigator: Associate Professor Zhu Chun Xiang, ECE

The main objective of this project is to develop a proactive hypertension diagnostic platform based on the well-developed CMOS technology by using multi metal ion sensors for sweat and pressure sensor for pulse rate. One of main challenges faced in the metal ion detection using ion selective field effect transistors for sweat lies in the poor drift performance due to the 3D open structure of metal oxide sensing layer which allows species in solution diffused to the sensing layer, causing the drift and error in the detection. In this project, we propose to develop high stable, high sensitive and high selective metal ion sensors with 2D stack sensing/diffusion barrier layers and dual gate structure. The proposed hypertension diagnostic platform can be assembled and integrated on either rigid or flexible substrate for wearable devices and can also be made for long term use or for disposable use. The developed platform may also be expanded to wider applications like preventing heat stoke or heat exhaustion by monitoring the change ions concentration in sweat.