Ejay Nsugbe
Papers
2
Total Citations
13
H-Index
2
About
Ejay Nsugbe is a researcher at the intersection of biomedical engineering and artificial intelligence, specializing in neural decoding and rehabilitation robotics. His work focuses on improving the quality of life for individuals with neurological impairments, particularly traumatic brain injury (TBI) and stroke survivors. Nsugbe’s major contributions include developing advanced signal processing and deep learning techniques to decode motor intent from EEG and high-density surface EMG (HD-sEMG) recordings. His highly cited 2021 paper introduces a linearly extendible multi-artifact removal approach for enhanced upper extremity EEG-based motor imagery decoding, a critical step for controlling rehabilitation robots. Another notable study applies deep learning to decode motion intent from HD-sEMG in TBI patients, demonstrating the potential for personalized, intelligent rehabilitation systems. With over 10 citations on his leading work, Nsugbe’s research is gaining recognition for its practical impact on active motor training and functional recovery. His achievements highlight a commitment to translating complex neural data into accessible, life-changing technologies for patients with severe motor disabilities.
Research Focus
Key Achievements
Top Papers
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