Mental Fatigue Detection

Definition

Mental Fatigue Detection examines the mechanisms, conditions and outcomes through which this factor shapes human cognition, learning, collaboration or sustainable performance in AI-supported settings.

Why this matters

Mental Fatigue Detection may materially affect human capability, independence, confidence, safety and productivity. Poorly designed assistance can create hidden costs even where short-term output appears to improve.

Research questions

Which behavioural and interaction signals can detect mental fatigue early enough to support timely intervention?

Hypotheses

A multimodal model combining response variability, correction behaviour and interaction rhythm will detect fatigue earlier than self-report alone.

Proposed methods

controlled task experiments; repeated-measures studies; ecological momentary assessment; interaction telemetry; interviews; pre-registered analysis; active comparison; subgroup and accessibility analysis; delayed retention or longitudinal follow-up; adverse-effect capture; reproducibility testing; participant debrief

Stakeholders and beneficiaries

cognitive scientists; occupational psychologists; human-factors engineers; employers; educators; workers; AI product teams; sleep scientists; shift-work safety managers