Sequential Neurofeedback via EEG Lead COV Ranking
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Solution Overview
Problem
Current low energy neurofeedback treatments do not optimize the order of treatment at different EEG leads, potentially limiting therapeutic efficiency.
Innovation Solution
The method involves attaching EEG leads to the patient's scalp, acquiring baseline EEG measurements, calculating the Fast Fourier Transform (FFT) for multiple time segments, determining the Coefficient of Variance (COV) for each lead, and providing neurofeedback in the sequence of higher to lower COV, selecting activity parameters based on predetermined criteria, and treating the sites with the greatest number of EEG sites meeting selection criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If neurofeedback treatment is provided at multiple EEG leads simultaneously, then treatment coverage is improved, but treatment efficiency is reduced due to lack of optimized sequencing
Solution Approach 1:
The patent segments the neurofeedback treatment into discrete sequential steps, where treatment is delivered to individual EEG leads one at a time rather than simultaneously. The system divides the multi-lead treatment into ordered segments based on COV calculations, treating each lead in sequence from highest to lowest COV value.
Solution Approach 2:
The patent performs preliminary analysis by calculating the Coefficient of Variance (COV) for each EEG lead before delivering treatment. This preliminary action ranks the leads in order of treatment priority, allowing the system to optimize the treatment sequence in advance based on measured brain activity variability.
2Device complexity
If treatment sequence is randomized or arbitrary, then device complexity is reduced, but measurement precision is lost in determining effective treatment order
Solution Approach 1:
The patent implements feedback by continuously monitoring EEG signals and calculating COV values for each lead. This feedback mechanism uses the measured variability in brain activity to dynamically determine and adjust the treatment sequence, ensuring that leads with higher variability are treated first.
Solution Approach 2:
The patent changes the treatment parameter from a fixed arbitrary sequence to a dynamic sequence based on COV values. By using COV as a quantitative parameter to rank leads, the system transforms the treatment order from static to adaptive, optimizing treatment based on real-time brain activity measurements.
Data Source
AI summary
The dominant brain wave frequencies of a patient are measured by an electroencephalogram (EEG) with a plurality of leads over the head and scalp. In a process for low energy neuro-feedback, the therapeutically beneficial low power RF field is sequentially applied via the same at a different frequency, which is generally offset from the dominant frequency by 5 to 20 Hz. The order of applying these low power stimuli to the different leads is optimized based on the activity observed at each lead and its variation over time. Leads positions having a greater Coefficient of Variation are treated first.