Papers
3
Total Citations
1,003
H-Index
3
About
Simone Elsig is a leading researcher in rehabilitation robotics, specializing in the development of non-invasive, naturally-controlled robotic hand prostheses. Her work focuses on advancing myoelectric control systems, which use surface electromyography (sEMG) signals to enable intuitive hand function for amputees. Elsig’s most influential contribution is her 2014 paper, “Electromyography data for non-invasive naturally-controlled robotic hand prostheses,” which has garnered 931 citations and serves as a foundational resource for the field. This work addresses the critical challenge of restoring lost hand functionality through machine learning-enhanced sEMG analysis, moving beyond traditional limited control methods. In her subsequent studies, including a 2016 paper with 66 citations, she explores how clinical parameters—such as muscle condition and amputation level—affect prosthetic control, providing essential insights for personalized device design. Elsig also investigates the impact of long-term prosthesis use on users’ control capabilities, highlighting the adaptive nature of human-machine interaction. Her research bridges engineering and clinical practice, offering practical pathways to improve the quality of life for hand-amputated individuals. Through her high-impact publications, Elsig has established herself as a key figure in advancing non-invasive myoelectric prosthetics.
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