<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/B0380400-7FD1-4FA3-99B5-6AF227BC7592" ns1:id="B0380400-7FD1-4FA3-99B5-6AF227BC7592"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/BDBECE8B-4FD6-46DC-B95F-76A6D76028C3" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/67CF9582-B341-4493-B341-0F7CAEC03EF7" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C8767B21-C9FE-4D9C-A9B3-63C6F8C09BAE" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/67CF9582-B341-4493-B341-0F7CAEC03EF7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/59B57D7D-64F1-4A60-A126-E03DA5B46AE5" ns1:rel="FUND" ns1:start="2024-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10131389</ns2:identifier></ns2:identifiers><ns2:title>Increasing the validity of cognitive state estimates in sim-racing and gaming.</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Affect IN has developed a technology to assess cognitive and affective state in near real-time by monitoring patterns of electrical brain activity from a wireless headset. This involves identifying idiosyncratic patterns of brain activity that can be monitored during gaming, enabling the cognitive state and well-being of the gamer to be assessed continuously. This provides data that can be used by the individual to maximise gaming performance and optimise well-being during gaming. However, classifying brain activity into different cognitive states is challenging and our estimates may diminish in accuracy over time. This project will allow Affect IN to work with the Newton Gateway to Mathematics to use cutting edge statistical and machine learning methods to refine the estimates of cognitive state, making our service more reliable, and our processes more efficient. This will support our aspirations to grow Affect IN rapidly to provide gamers with targeted support to improve performance and optimise well-being.</ns2:abstractText></ns2:project>