91porn

The EEG is a promising approach that can be used to assess quality implicitly. Unlike traditional subjective methods using the Mean Opinion Score (MOS), the EEG provides valuable insight into the link between perceived quality and how the user feels at the physiological level. However, there is a need to better understand the nature of the recorded neural signals and their associations with user-perceived quality. Nevertheless, the EEG can provide additional and complementary information that will aid understanding of human perception of content. Furthermore, it has the potential to facilitate real-time monitoring of QoE.

This project focuses on applying artificial intelligence-based data analysis techniques to identify blood-based biomarkers that may assist in the identification of early disease subjects and predicting likely course of the disease progression. Blood-based methods may serve as a cost-effective and non-invasive approach that may be implemented in point-of-care devices to complement more sophisticated approaches.

Initially this project has focussed on the familiarisation of the fabrication techniques which include photolithography, sputtering, plasma and chemical etching and evaporation. These techniques have been applied on many occasions to fabricate several sets of GFETs from graphene samples provided by various collaborators including the University of Cambridge. Once the standard procedures for the measurements to characterise the electrical and structural properties of the GFETs are completed, the focus of this project over the course of the next six to twelve months will be on the bio-functionalisation of GFETs and antennas.

We have developed both back gated graphene field effect transistors (gFETs) and modified screen printed electrodes (SPEs) for the detection of important neurochemical indicators of AD such as Aβ1-42 and Clusterin. The measurements for gFETs are done with Keysight parameter analyser interfaced to a 4-probe station and for SPEs is done using Dropsens Analyser. The developed sensing platforms are highly sensitive and provide a tool for the rapid and reliable detection of biomarkers for minimally invasive, cost and time effective point of care diagnostic devices.