MUMBAI, India, Sept. 12 -- Intellectual Property India has published a patent application (202411012852 A) filed by Bennett University, Greater Noida, Uttar Pradesh, on Feb. 22, 2024, for 'deep learning for decoding neural signals in brain-computer interface.'
Inventor(s) include Prof. Ajith Abraham; and Prof. Arpit Bhardwaj.
The application for the patent was published on Sept. 12, under issue no. 37/2025.
According to the abstract released by the Intellectual Property India: "This patent describes a method and system for decoding neural signals in a brain-computer interface (BCI) system. The method involves receiving raw neural signals from a user's brain using an array of sensors, preprocessing the signals to remove noise and artifacts, transforming the preprocessed signals into a feature set, and inputting the feature set into a deep learning model trained to decode the neural signals. The decoded neural signals are then outputted to control an external device or application. The system includes the array of sensors, a signal processing module, and a deep learning model. The system can be used to control an external device or application, such as a computer cursor or a robotic arm. Real-time feedback is provided to the user based on the decoded neural signals, which can improve their control over the external device or application. The patent also covers the types of sensors used, preprocessing techniques, feature extraction, deep learning models, and feedback modules used in the BCI system."
Disclaimer: Curated by HT Syndication.
