Papers
9
Total Citations
126
H-Index
6
About
David Guiraud is a leading researcher in assistive neurotechnologies, specializing in human-machine interfaces, functional electrical stimulation (FES), and neuromuscular modeling for individuals with spinal cord injury (SCI) and tetraplegia. His major contributions include developing a novel EMG-based interface that enables people with tetraplegia to pilot robot hand grasping using residual supra-lesional muscle contractions—a breakthrough demonstrated in a 2016 study (32 citations) with five SCI participants. He has advanced EMG-to-force estimation through full-scale physiology-based muscle models (2009, 26 citations), improving the accuracy of prosthetic and exoskeleton control. Guiraud’s work on FES includes nonlinear identification methods for muscle property variation (2010, 8 citations) and optimal stimulation pattern synthesis for knee joint control (2008, 6 citations), directly impacting rehabilitation robotics and implanted neuroprostheses. His research, spanning from modeling the paralyzed lower limb (2004) to classifying upper limb movements for neuroprosthesis interfaces (2018), has garnered over 120 total citations, reflecting its significance in restoring motor function and enhancing quality of life for individuals with paralysis.
Research Focus
Key Achievements
Top Papers
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- 3EMG-to-force estimation with full-scale physiology based muscle model26 citations · 2009
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- 6Modelling of the human paralysed lower limb under FES7 citations · 2004
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- 9From neuroprosthetics to implanted FES control architecture2 citations · 2008