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Measures response latency under controlled conditions
A web-based system that measures cognitive performance through short behavioural tasks and tracks how responses change over time using a personal baseline model.
Longitudinal cognitive tracking
Personal baseline model
Most cognitive tools rely on single-session scores or population averages. These approaches fail to capture how cognitive performance fluctuates over time — and they cannot distinguish meaningful change from normal day-to-day variation within a given individual.
iBrain Gym introduces a measurement approach that compares each session against the user's own established baseline — not against population norms. This makes it possible to detect changes that are meaningful for that individual.
Measures response latency under controlled conditions
Short-term recall tasks with variable load
Task-switching and inhibition measures
Within-subject model built from repeated sessions
Statistical thresholds distinguish meaningful shifts from noise
Three short tasks covering reaction speed, working memory, and cognitive flexibility — completed in under a minute.
Z-scores, standard error of measurement, and trend analysis calibrated to each user's own baseline.
Statistical thresholds flag meaningful changes across sessions, distinguishing signal from normal variation.
OpenAI-powered summaries translate raw scores into clear, readable session insights.
Face verification and liveness detection via BioID, combined with OTP authentication through Twilio.
iBrain Gym enables users to understand their cognitive consistency over time, rather than relying on static scores. By building a personal baseline and applying statistical change detection, the system surfaces patterns that would otherwise remain invisible in single-session assessments.
iBrain Gym is developed under iBrain Lab — a research and product initiative focused on behavioural measurement and cognitive pattern analysis.