Rahul Upadhyay

Thapar Institute of Engineering & Technology, Indian Institute of Information Technology Design and Manufacturing Jabalpur

Papers

Total Citations

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About

Rahul Upadhyay is a researcher at the forefront of non-invasive Brain-Computer Interface (BCI) technology, with a focus on transforming assistive devices and human-machine interaction through electroencephalography (EEG). His work centers on decoding neural signals—particularly P300 responses and imagined motor movements—to enable direct brain control of external systems, from robotic arms to wheelchairs. Upadhyay’s most cited work, a systematic review on visual stimuli-evoked P300 BCIs (20 citations), highlights how these systems are revolutionizing applications in medicine, rehabilitation, and entertainment by providing reliable communication channels for patients with severe disabilities. His foundational studies on feature extraction and classification of motor imagery EEG signals (8 citations) and robot motion control via BCI (4 citations) established key methodologies for improving system accuracy and efficiency. Notably, his recent development of PyNoetic, a modular Python framework for no-code BCI development, addresses critical gaps in existing tools by offering stage-wise flexibility, making advanced BCI technology accessible to non-specialists. With contributions spanning foundational signal processing to practical, user-friendly frameworks, Upadhyay is driving the evolution of BCIs from laboratory concepts to real-world assistive technologies.