Md. Shafivulla

Papers

Total Citations

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About

Md. Shafivulla is a researcher whose work lies at the intersection of biomedical signal processing and assistive robotics, with a particular focus on surface electromyography (sEMG) for human-computer interfaces. His most cited paper, "sEMG based human computer interface for robotic wheel" (2012), introduces a real-time system that interprets hand gesture sEMG signals using artificial neural networks to control a robotic wheelchair. By capturing raw signals from an 8-channel sEMG amplifier and NI-DAQ card, Shafivulla developed a pattern recognition framework that enables intuitive, non-invasive control—a critical step toward restoring mobility for individuals with severe motor impairments. This foundational work, which has garnered 2 citations, demonstrates his ability to merge hardware integration with machine learning for practical assistive technologies. His contributions highlight the potential of biosignal-driven interfaces to enhance quality of life, and his research continues to inspire advances in rehabilitation engineering and human-robot interaction.