Multisensory EEG Assessment for Objective mTBI Detection
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Solution Overview
Problem
Current methods for assessing mild traumatic brain injury (mTBI) and neurodegenerative diseases like Alzheimer's and Parkinson's are limited by the need for behavioral responses, which are susceptible to biases such as motivation, education, and language, and lack objective, direct neurophysiological measures.
Innovation Solution
A system using olfactory, auditory, and somatosensory stimulation in conjunction with EEG measures to generate OEPs and OERPs, along with resting EEG, to create a composite index (OCI) that assesses brain function without requiring behavioral responses, incorporating a handheld device for data collection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If behavioral/perceptual olfactometry studies are used to assess olfactory function, then the assessment can provide detailed perceptual information, but the test is adversely susceptible to experience, motivation, educational level, language, and patient cooperation
Solution Approach 1:
The patent replaces the behavioral/mechanical response system with an electrophysiological measurement system. Instead of relying on patient-reported perceptual responses to olfactory stimuli, the system measures electrical potentials (OEPs and OERPs) generated by the olfactory system and brain in response to odorant stimulation. This substitution eliminates susceptibility to motivation, education, language, and cooperation factors while maintaining assessment accuracy.
Solution Approach 2:
The patent changes the measurement parameter from behavioral/perceptual reports to electrophysiological signals. By measuring electrical potentials in the olfactory epithelium and brain rather than relying on patient responses, the system transforms the assessment into an objective physiological measurement that is not influenced by patient characteristics or cooperation levels.
2Reliability
If electrophysiological measures (OEPs and OERPs) are used to assess olfactory function, then the assessment becomes objective and comparable to otoacoustic emissions and auditory brainstem responses, but the system complexity increases requiring specialized equipment and protocols
Solution Approach 1:
The patent employs standard EEG electrodes and electrophysiological recording equipment that are already widely used in clinical and research settings. By utilizing existing universal equipment rather than developing specialized devices, the system achieves objective electrophysiological measurement while minimizing the increase in device complexity. The same equipment can be used for multiple neurological assessments.
3Adaptability or versatility
If multiple concurrent neurophysiological measures are integrated into a composite index, then the assessment provides comprehensive brain function evaluation, but the data processing and analysis complexity increases
Solution Approach 1:
The patent combines multiple neurophysiological measures (OEPs, OERPs, and resting EEG measures including alpha, beta, gamma, delta and theta frequency oscillations) into a single composite index. This merging of multiple data streams provides comprehensive brain function evaluation while consolidating the analysis into one integrated metric, thereby managing data processing complexity through synthesis rather than separate analysis of each component.
Data Source
AI summary
A method includes accessing EEG data obtained from each of a first plurality of subjects and from each of a second plurality of subjects, and training a machine learning model to identify a brain state associated with mild traumatic brain injury (mTBI) using the EEG data for each of the first plurality of subjects. The first plurality of subjects are known to have mTBI, and the second plurality of subjects are known to be mTBI unafflicted. The EEG data for each subject includes EEG data for the subject at rest and sensory evoked response EEG data for the subject. A system for identifying a brain state of a subject includes a portable odorant generation and EEG recording system, and at least one processor configured to use a trained machine learning model to analyze EEG data obtained by the EEG recording system to identify the brain state of the subject.