Mamunur Rashid

Universiti Malaysia Pahang Al-Sultan Abdullah

Papers

Total Citations

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About

Mamunur Rashid is a researcher focused on brain-computer interfaces (BCI) and assistive robotics, particularly for mobility-impaired individuals. His work centers on developing cost-effective, non-invasive systems that translate neural signals into real-world control. In his most-cited study, "Investigating the Possibility of Brain Actuated Mobile Robot Through Single-Channel EEG Headset" (2020, 7 citations), Rashid demonstrated that a single-channel EEG headset could reliably control a mobile robot, significantly lowering the barrier to BCI technology. He further advanced this line of inquiry with "Offline EEG-Based DC Motor Control for Wheelchair Application" (2020, 2 citations), where he explored offline signal processing for precise motor control, directly targeting wheelchair automation. These contributions highlight his commitment to accessible, practical BCI solutions that can improve quality of life for those with severe motor disabilities. By prioritizing single-channel systems, Rashid’s work reduces cost and complexity, making BCI-driven mobility aids more feasible for widespread clinical and home use. His research bridges neuroscience, signal processing, and robotics, offering a clear pathway from lab experiments to real-world assistive devices.