Developing an interpretable, low-burden machine-learning approach to estimate mental fatigue and its effect on decision quality in team field sports, using non-intrusive signals captured during routine training.
Overview
Mental fatigue impairs attentional control and decision quality in team field sports, yet day-to-day assessment still relies largely on self-report or complex laboratory procedures. EYESPEAK is developing and validating an interpretable Mental Fatigue Score derived from low-burden, non-intrusive signals that can be captured within normal training — designed to sit alongside existing readiness screens rather than replace them.
The emphasis is on being scalable, adaptive and privacy-respecting: producing clear, coach-facing guidance to support welfare-aligned training decisions, while handling athlete data under strong governance (GDPR-aligned, anonymised feature schemas).
Funding & team
Funded under the SETU President’s Award (€125,000). Led by Dr. Omer Ali (Principal Investigator), with Dr. Paula Fitzpatrick (South East Technological University) and Dr. Frances Cleary (Walton Institute, SETU) as co-investigators.
More detail on methods and findings will be shared as the project progresses.
Dr. Paula Fitzpatrick
Co-Investigator
South East Technological University
Dr. Frances Cleary
Co-Investigator
Walton Institute
Yuyao Wang
PhD Student
South East Technological University