Opportunity Overview
The project addresses the challenge of creating an objective, reliable, and clinically applicable method for pain assessment. A key component is the systematic collection of EEG data during colonoscopies, which provides an ideal setting due to its standardized nature and predictable pain occurrences. This approach facilitates the application of advanced machine learning techniques to identify reliable EEG biomarkers of pain, with the potential to generalize across patients.
EEG is a non-invasive, cost-effective, portable and easy to perform method that records electrical signals from the brain using electrodes placed on the scalp. These electrodes detect the brain’s electrical activity which is commonly used to diagnose conditions such as epilepsy, brain injuries and sleep disorders. The time resolution of EEG is very high and allows capturing the dynamics of pain perception in real-time. This makes EEG the ideal method for developing an objective measure of pain. Previous studies have shown that pain perception changes the electrical activity of the brain. However further research is needed to standardise EEG-based measures of pain and realise their potential in clinical settings.
The project's objectives include (1) collecting comprehensive EEG data during colonoscopies, (2) using machine learning to identify pain biomarkers, and (3) facilitating the translation of objective pain measurements into clinical practice by obtaining feedback from clinicians and patients and immersing the...
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Start FreeSolicitation Details
| Issuing agency | EPSRC |
|---|---|
| Country | United Kingdom |
| Category | Research Development |
| Published | August 31, 2025 |
| Procurement stage | Active solicitation |
| Response due | August 31, 2028 |
| Status | Open — accepting responses |
| Official source | View original notice |
| Last verified | August 10, 2026 |
Source: UK Research and Innovation (UKRI) — Open Government Licence v3.0.
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