Sridhar Krishnan

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About

Sridhar Krishnan is a leading researcher in biomedical signal processing and brain-computer interfaces (BCIs), with a specific focus on lower-limb rehabilitation. His work centers on developing intelligent systems that decode motor imagery from electroencephalogram (EEG) signals, enabling more intuitive and effective neurorehabilitation technologies for patients with mobility impairments. Krishnan’s major contributions include pioneering subject-specific approaches to improve BCI performance. His 2019 paper on recognizing pedaling motor imagery (49 citations) introduced an unsupervised feature extraction method using spectrograms to enhance EEG pattern discrimination. In another highly cited 2019 work (48 citations), he proposed a novel subject-specific EEG channel selection technique using non-negative matrix factorization, significantly reducing computational load while maintaining high recognition accuracy for lower-limb motor imagery. These contributions address critical challenges in BCI design—namely, the need for personalized, efficient, and clinically viable systems. Krishnan’s research has substantial impact in the rehabilitation engineering community, with his work informing the development of adaptive, user-centric neuroprosthetics. His achievements highlight a commitment to translating signal processing innovations into practical solutions that restore motor function and improve quality of life for individuals with neurological injuries.