Papers
1
Total Citations
4
H-Index
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About
Susanne Dyck’s research lies at the intersection of neural engineering, motor control, and human-computer interaction, with a primary focus on advancing invasive brain-computer interfaces (BCIs) for severely paralyzed individuals, such as tetraplegics. Her most-cited work, “Quantifying the alignment error and the effect of incomplete somatosensory feedback on motor performance in a virtual brain–computer-interface setup,” systematically dissects the critical factors limiting BCI performance—namely, alignment error between decoded and intended movements, and the absence of natural somatosensory feedback. By developing a virtual experimental framework, Dyck demonstrated how these deficits degrade motor control, offering a quantitative foundation for improving BCI design. Her contributions are pivotal for translating neural decoding into practical, real-world control of robotic limbs, directly addressing the quality-of-life needs of patients. With 4 citations on this key paper, her work is gaining traction among researchers seeking to close the loop between brain signals and sensory feedback. Dyck’s rigorous approach to quantifying performance bottlenecks marks her as a rising voice in neuroprosthetics, where her insights promise to shape more intuitive and effective assistive technologies.
Research Focus
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Top Papers
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