EEGAUAI - EEG Analysis Using Artificial Intelligence
Initial situation
Ensuring an objective assessment and reliable determination of medical and psychological reports is of considerable financial and social importance. Such reports are usually prepared on behalf of courts, authorities and (social) insurance providers in order to examine test persons with regard to their entitlement to benefits and correct social insurance care (e.g. after accidents or in the event of illness). To date, no efforts have been made to integrate objective electrophysiological data and AI-supported solution approaches into validation tests for complaints.
Solution idea
It is proposed to use electrophysiological measurements (EEG) to assess the willingness of test subjects to exert effort in expert evaluation situations. Signal analysis algorithms and AI methods (machine learning) are to be developed and implemented in order to enable an automated software pipeline for signal cleansing and objective classification of the willingness to exert effort.
Benefit
Our aim is to provide objective methods for determining and classifying the willingness to make an effort in medical and psychological assessments in future, which comply with the applicable legal and psychological-medical standards. Ensuring valid medical and psychological assessments is of considerable financial and social importance in order to secure benefit entitlements and guarantee appropriate social security provision.
Implementation of the AI application
Electroencephalographic (EEG) measurement series derived during a visual stimulus-response time task are used to develop the innovation. The Exploring Project focuses on the development of an automatable software pipeline for EEG pre-processing. In subsequent steps, the electrophysiological data collection methods will be combined with AI-based algorithms (machine learning) for the objective classification of effort readiness in the neuropsychological tests.