MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202641091042 A) filed by Mohan Babu University on July 27, 2026, for Quantum-Assisted Eeg Classification System For Pediatric Epilepsy Detection.

Inventors include Dr. A. V. Sriharsha; Mr. V. Siva Praneesh; Mr. U. Chaithanya Nani; Mr. V. Jaya Prakash; and Mr. P. Tarun Sai.

The application for the patent was published on July 31, 2026, under issue no. 31/2026.

Abstract: The present invention relates to a quantum-assisted electroencephalogram (EEG) image classification system for automated pediatric epilepsy detection. The disclosed system integrates EEG signal preprocessing, frequency band decomposition, topographic image generation, convolutional neural network-based feature extraction, and Quantum Support Vector Machine (QSVM) classification within a unified diagnostic framework. Initially, EEG recordings undergo artifact removal, normalization, segmentation, and signal enhancement before being converted into scalp topographic images representing spatial brain activity. The generated images are processed by a convolutional neural network to extract meaningful neurological features, which are subsequently encoded into a quantum feature space and classified using a Quantum Support Vector Machine. The hybrid quantum-classical architecture improves seizure detection accuracy, enhances robustness against noisy EEG recordings, minimizes computational complexity, and provides superior classification performance compared with conventional machine learning approaches. The modular system architecture supports integration with hospital information systems, cloud healthcare platforms, wearable EEG devices, telemedicine infrastructure, and future quantum computing technologies. The invention provides a reliable, scalable, and efficient clinical decision support system capable of assisting neurologists in the early diagnosis of pediatric epilepsy while improving patient care and reducing diagnostic time.

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