MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043107 A) filed by Sr University, Warangal, Telangana, on April 4, for 'brain-computer interface system using agentic artificial intelligence agents for personalized neural command generation.'

Inventor(s) include Dr. M. Thangamani; Dr. Sandip Bhattacharya; Dr. V. Sabapathi; Dr. V. Ravindra Krishna Chandar; and Dr. Sudip Bhattacharya.

The application for the patent was published on April 17, under issue no. 16/2026.

According to the abstract released by the Intellectual Property India: "Brain-Computer Interface System Using Agentic Artificial Intelligence Agents for Personalized Neural Command Generation ABSTRACT This invention introduces an advanced Brain-Computer Interface (BCI) system that leverages Agentic Artificial Intelligence (AI) agents to personalize and optimize the generation of neural commands for external devices or applications. Existing BCIs often face challenges such as poor robustness, high calibration demands, and inability to adapt to individual users over time. The proposed system addresses these issues by incorporating a modular AI architecture where various functional agents work together to process neural signals, decode intent, adapt to user preferences, and ensure safety. The system features a neural signal acquisition module, a preprocessing and feature extraction unit, an AI orchestration module, and several specialized agents including quality, intent decoding, adaptation, safety enforcement, and explanation agents. These agents interact dynamically, creating a personalized neural command vector that is context-sensitive and user-specific. The system not only supports real-time adaptation based on user feedback but also enforces strict safety and policy constraints, making it suitable for applications in assistive technologies, prosthetics, and rehabilitation. The integration of these intelligent agents results in a more reliable, transparent, and user-friendly BCI, with significant improvements in stability, accuracy, and performance over traditional systems."

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