Hammad Nazeer

Papers

Total Citations

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About

Hammad Nazeer is a researcher specializing in biomedical signal processing, assistive robotics, and noninvasive brain–computer interfaces (BCIs). His work focuses on developing intuitive control systems for prosthetic devices and exploring multimodal neural interfaces. His most cited paper, "EMG Based Control of Individual Fingers of Robotic Hand" (2018, 16 citations), presents a novel approach to enhancing prosthetic hand dexterity by using eight-channel surface electromyography (sEMG) to decode individual finger movements from forearm muscle activity across ten subjects. This contribution addresses a critical challenge in rehabilitation robotics—achieving fine-grained, natural control of robotic hands. More recently, Nazeer has advanced the field of noninvasive BCIs with his 2024 study on hybrid EEG-fNIRS systems, which combines functional near-infrared spectroscopy and electroencephalography to improve signal robustness and classification accuracy. While still early in its citation impact, this work signals a promising direction for reliable, real-world BCI applications. Nazeer’s research bridges engineering and clinical needs, aiming to restore motor function and enhance human–machine interaction for individuals with disabilities.