MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202541108680 A) filed by Priyadarshan; Dr. C. Infant Vinoth; Mr. S. Mohammed Sudir; Mr. M. Muthu Gokul; Mr. S. P. Surya Sankar; Dr. G. Sundar; and Dr. R. Senthilkumar, Coimbatore, Tamil Nadu, on Nov. 10, 2025, for 'neurochair: electromyography signal acquisition and processing for assistive wheelchair.'
Inventor(s) include Priyadarshan; Dr. C. Infant Vinoth; Mr. S. Mohammed Sudir; Mr. M. Muthu Gokul; Mr. S. P. Surya Sankar; Dr. G. Sundar; and Dr. R. Senthilkumar.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "NeuroChair: Electromyography Signal Acquisition and Processing for Assistive Wheelchair presents an innovative approach to wheelchair automation using bioelectrical signals generated by human muscles. The system is designed to aid individuals with severe physical disabilities who are unable to operate conventional wheelchairs using joysticks or buttons. It employs two Electromyography (EMG) sensors, one attached to the left arm and the other to the right arm, to detect muscle contractions and convert them into control signals. When the user flexes the left-hand muscle, the wheelchair turns left; when the right-hand muscle is contracted, it turns right; and when both muscles are contracted simultaneously, the wheelchair moves forward. The EMG signals, being low in amplitude, are first amplified and filtered through the EMG sensor module before being processed by a microcontroller, which interprets these signals and sends corresponding commands to the motor driver (L293D) that controls the motion of the DC motors. To enhance safety, Infrared (IR) sensors are integrated to detect obstacles, automatically stopping the wheelchair when an obstruction is present. A DC-DC buck converter module (LM2596 HW-411) is used to provide a stable and regulated power supply from a 12V battery, ensuring reliable operation of all components. The proposed system demonstrates how biomedical signal acquisition and embedded control technology can be effectively integrated to create an intelligent assistive device that enhances mobility, safety, and independence for differently-abled individuals. This project highlights the potential of EMG-based control systems in the field of rehabilitation engineering and serves as a foundation for future advancements such as wireless connectivity, adaptive control using artificial intelligence, and Internet of Things (IoT) integration to further improve the functionality and user experience of assistive wheelchairs."
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