Janith Sandaruwan

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About

Janith Sandaruwan is a researcher advancing brain-machine interfaces (BMIs) and assistive robotics, with a focus on restoring independence for individuals with motor disabilities. His most-cited work, "Motor Imagery EEG-EOG Signals Based Brain Machine Interface (BMI) for a Mobile Robotic Assistant (MRA)" (2019), integrates electroencephalography (EEG) and electrooculography (EOG) signals to enable intuitive control of a mobile robotic assistant—a wheelchair paired with a custom manipulator. This system allows users to navigate and interact with their environment using imagined movements and eye signals, bridging neural decoding with real-world mobility. With 7 citations, the paper demonstrates early impact in the field of non-invasive neural control. Sandaruwan’s contributions lie in fusing multimodal biosignals to create practical, user-centric assistive devices, addressing critical gaps in daily living support for disabled populations. His work stands at the intersection of signal processing, robotics, and rehabilitation engineering, offering a scalable framework for future BMIs. For students and researchers, Sandaruwan exemplifies how targeted, application-driven research can translate complex neural data into tangible improvements in quality of life.