3D Human Head Parametric Estimation and EEG Localization with 2D Azimuthal Equidistant Map Projection

The diagnostic procedure that involves attaching electrodes at distinct points on the human head to detect and analyze electrical signals of brain activity is known as Electroencephalography (EEG). Previously,we proposed an algorithm for computerized EEG electrode position prediction that is substantially faster and more accurate than the current traditional method of calculating and marking these positions. This paper proposes an alternate and revised approach for estimating the optimal electrode position that is more robust, effective and less susceptible to errors. This new approach utilizes the 3D ellipsoid model of human heads and is based on the Earth’s Map projection and location identification. Similar ideas are adapted for predicting the optimal positions of the EEG electrodes’ placements on the human head. The proposed approach is implemented and compared to the results from the algorithm in our previous work. The findings from the experimental studies show that the proposed approach is more efficient than the algorithm described in our previous work, with better RMSE under simulated angular tilts, more resilient with 70% more exact prediction under simulated noise and accurate with an average RMSE of around 2 cm or less.