MUMBAI, India, Aug. 12 -- Intellectual Property India has published a patent application (202611079525 A) filed by Ajay Kumar Garg Engineering College on June 28, 2026, for Machine Learning-Based System For Eeg-Based Behavioral Brain Dysfunction Analysis And Working Method Thereof.
Inventors include Yukti Garg; Shifa Saeed; Siddhant Sharma; Vyom Rastogi; and Ms. Aastha Sharma.
The application for the patent was published on August 07, 2026, under issue no. 32/2026.
Abstract: The present invention discloses a machine learning-based system for electroencephalography-based behavioral brain dysfunction analysis and working method thereof. The system comprises a multi-channel electroencephalography signal acquisition and analog front-end module (100) configured to acquire neural signals from a subject, an adaptive signal pre-processing and artifact rejection module (200) configured to eliminate physiological and environmental noise, a multi-domain feature extraction engine (300) configured to derive temporal, spectral, nonlinear, connectivity, and graph-based neural biomarkers, and an ensemble deep learning classification framework (400) configured to classify behavioral brain dysfunction conditions. The system further comprises a behavioral phenotyping module (500), a multi-modal data fusion engine (600), an explainability and neuroanatomical localization module (700), a cloud-based clinical decision support interface (800), and a centralized system controller (900). The invention enables automated, accurate, explainable, and multi-modal diagnosis of behavioral brain dysfunctions with enhanced clinical decision support. Accompanied Drawings [Fig. 1-4]
Disclaimer: Curated by HT Syndication.
