<?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="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/23F08C44-4015-49B5-87C4-52C3DA19235C" ns1:id="23F08C44-4015-49B5-87C4-52C3DA19235C"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/980D5E43-8D92-4778-BC74-228DEF02008E" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/980D5E43-8D92-4778-BC74-228DEF02008E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2017-05-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/86E9920D-CF13-4444-9570-5CDA59508745" ns1:rel="FUND" ns1:start="2016-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">132050</ns2:identifier></ns2:identifiers><ns2:title>Feasibility of emotion detection via facial muscle activity sensors embedded in glasses frame - FEDEm-Glasses</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>We have developed novel, miniaturised muscle activity sensors that work without the need for invasive procedures. We aim to integrate these into a glasses frame. In combination with a six-axis motion sensor (gyroscope and accelerometer) we want to demonstrate:
-Detection of corrugator (frown) muscle activity, without drawbacks of EMG (skin preparation, obtrusive caps)
-Accurate detection of head position, without drawbacks of remote cameras (occlusion, reference objects)
-Gesture recognition through a combination of the above
-Assessment of emotional state, through head position and corrugator response to IAPS images
-Performance compared to conventional EMG technology
This work could lead to gesture activated devices, enhanced software that detects user engagement and entertainment that detects emotional state of the user.</ns2:abstractText></ns2:project>