Mark van de Ruit
Papers
2
Total Citations
18
H-Index
2
About
Mark van de Ruit is a researcher focused on understanding and quantifying human motor control, particularly in the context of upper limb impairments. His key research areas include system identification, joint impedance estimation, and the application of advanced computational methods to characterize motor function. Van de Ruit's major contributions involve developing novel techniques to reveal time-varying joint impedance during movement, using kernel-based regression and nonparametric decomposition—a method that captures how humans continuously regulate joint stiffness to optimize performance and minimize control effort. This work, published in 2018 with 15 citations, provides critical insights into the neural mechanisms underlying movement. Additionally, his 2023 study on system identification demonstrates a feasible, reliable, and valid approach to quantify upper limb motor impairments in hemiparetic arms, addressing the limitations of traditional clinical scales. By leveraging robotics and dynamic modeling, van de Ruit offers a more objective and sensitive tool for assessing motor deficits, with potential applications in rehabilitation and neuroprosthetics. His research bridges engineering and neuroscience, advancing our understanding of motor impairment and recovery.
Research Focus
Key Achievements
Top Papers
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