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Brain’s excessive debris discernible by adaptive wavelet transform made of Faraday coils of electroencephalograph


MOJ Applied Bionics and Biomechanics
Harold H Szu,1T Julian Chu2
The Catholic University, USA

Abstract

The key point relevant to our proposed studies concentrates on the fluctuation of Electroencephalograph (EEG). First of all, EEG is not a wave of any kind, not electromagnetic, nor acoustic, but simply the magnetic field disturbance generated by Right Hand Rule of Ampere law following those Calcium ion currents along each neuronal axons where the fingers curl around magnetic field lines, Then, these mixtures of magnetic field lines are never intersecting one another and find themselves outside the scalp and picked up by two orthogonal miniature Faraday coils called the Faraday induction electric generators. We wish to know the collective frequency of these transient currents we propose an efficient Adaptive Wavelet Transform (AWT) which is a single kernel computed off-line by the Least Mean Square Sense using Artificial Neural Networks (ANN). The fluctuations are likely attributed by the inhomogeneous neuro-glia cells conducting the housekeeping of toxic debris or deposits cleaning. Aging brain might be characterized by several brain disorders which are lacking of household noninvasive monitoring system, which we propose two orthogonal Faraday coils, and on-line AWT through Smartphone communication to the nurses and physicians. For example, the cognitive decline, dementia and potential Alzheimer’s disease, epileptic seizures, bi-polar might be due to the long time accumulation of toxic waste; e.g., beta-Amyloid [2]. For our proposed feasibility studies, we have developed a model of adaptive wavelet transform at the compressive sensing of high-density (about 8 ~16) needle electrodes that can connect to a Smartphone for a real time display of the EEG electrodes. Furthermore, we will offer a super-resolution by the wavelets extrapolation and interpolation cross the brain. (2018 Continued Resolution support for “Gulf Coast Deep Learning at Lafayette LA” during Oct 26-27, 2018 (cf. http://www.ica-wavelet.org)

Keywords

complex, baby boomers, brain debris, midcentury, seniors, noninvasive, Glymphatic, neurologic, diseases, Smartphone, electric, elucidates, mechanisms, explore, drainage

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