Methods for estimating neuropsychiatric activity
By quantifying eye movement complexity and pupil diameter using multiscale entropy analysis, the method effectively estimates neuropsychiatric activity, enhancing diagnostic accuracy for developmental and mental disorders.
JP2026109911APending Publication Date: 2026-07-02NAT CENT OF NEUROLOGY & PSYCHIATRY +1
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- NAT CENT OF NEUROLOGY & PSYCHIATRY
- Filing Date
- 2024-12-20
- Publication Date
- 2026-07-02
AI Technical Summary
Technical Problem
Existing methods lack accurate estimation of developmental and mental disorders based on eye movement complexity and pupil diameter, despite the overlap of brain regions involved in these conditions.
Method used
A method that quantifies the complexity of eye movements and time-averaged pupil diameter to estimate neuropsychiatric activity, using multiscale entropy analysis and time-series data from eye trackers to classify subjects with high accuracy.
Benefits of technology
Enables accurate estimation of developmental disorders like ADHD and mental disorders by analyzing eye movement complexity and pupil diameter, improving diagnostic accuracy through high-precision classification.
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Smart Images
Figure 2026109911000001_ABST
Abstract
This invention provides a method for estimating neuropsychological activity that can accurately predict developmental disorders, mental illnesses, and other conditions. [Solution] Time-series data of the subject's pupil diameter and time-series data of the subject's eye movements are obtained. The time-averaged value of the pupil diameter is calculated from the time-series data of the pupil diameter, and the complexity of eye movements for each time scale is quantified from the time-series data of eye movements. Based on the time-averaged value of the pupil diameter and the complexity of eye movements, the subject's neuropsychiatric activity is estimated.
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