Jacob Gusman

Jacob Gusman

Jacob Gusman received the B.Sc. degree in biomedical engineering from the University of Rochester, Rochester, NY, in 2016. He is currently working toward the Ph.D. degree in neural engineering at Brown University, Providence, RI.

Between 2012 and 2016 he spent five summers working as a Student Intern at Draper Laboratory, Cambridge, MA, and in 2015 was a Research Assistant in the Carney Laboratory at the University of Rochester. In 2016, he received the Whitaker International Fellowship whereby he spent a year with the Biomechatronics and Neurorehabiliation Laboratory at Chalmers University of Technology, Gothenburg, Sweden. His research interests include biological signal processing, prosthetic control, and brain-machine interfaces.


Contributions

  • Evaluation of Computer-Based Target Achievement Tests for Myoelectric Control
    Evaluation of Computer-Based Target Achievement Tests for Myoelectric Control

    Real-time evaluation of novel prosthetic control schemes is critical for translational research on artificial limbs. Recently, two computer-based, real-time evaluation tools, the target achievement control (TAC) test and the Fitts’ law test (FLT), have been proposed to assess real-time controllability. Whereas TAC tests provides an anthropomorphic visual representation of the limb at the cost of confusing visual feedback, FLT clarifies the current and target locations by simplified non-anthropomorphic representations. Here, we investigated these two approaches and quantified differences in common performance metrics that can result from the chosen method of visual feedback.

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