Dilbag Singh

Gwangju Institute of Science and Technology

Papers

Total Citations

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About

Dilbag Singh is a researcher specializing in rehabilitation robotics, biomedical signal processing, and machine learning applications for assistive technology. His work sits at a critical intersection of artificial intelligence and medical engineering, with a particular focus on improving the quality of life for individuals with neuromuscular disorders, musculoskeletal conditions, and limb amputations. Singh's most notable contribution, a 2021 overview on machine learning in human arm rehabilitation via exoskeleton robots (18 citations), has established him as a meaningful voice in the growing field of therapy robotics. This work synthesizes how intelligent systems can support and restore motor functionality, providing a valuable reference for researchers and clinicians navigating this rapidly evolving domain. Building on this foundation, his 2022 study introduced a hybrid CNN-SVM architecture for classifying surface electromyography (sEMG) signals — a technically demanding challenge central to enabling precise robotic rehabilitation of upper limbs and hands. With 8 citations, this paper demonstrates his ability to translate deep learning innovations into practical biomedical solutions. Together, Singh's research reflects a coherent and ambitious research agenda: harnessing machine learning to make rehabilitation robotics smarter, more responsive, and ultimately more effective for patients worldwide.