Nicholas Tacca
Papers
4
Total Citations
50
H-Index
4
About
Nicholas Tacca is a rising leader in neural engineering and human–machine interaction, whose work bridges wearable sensing, robotic prosthetics, and collaborative robotics. His research centers on decoding human intent—from muscle activity to brain signals—to create intuitive, adaptive assistive technologies. Tacca’s most cited paper introduces a high-density EMG forearm sleeve with up to 150 electrodes, achieving remarkable accuracy in complex hand gesture classification and continuous joint angle estimation (24 citations, 2024). This innovation promises to transform human–computer interaction by providing a natural, high-resolution interface. He also proposed CyberLimb, a novel robotic prosthesis concept that shares control between user and machine to reduce cognitive load (13 citations, 2022). In human-robot collaboration, Tacca demonstrated how anticipatory brain responses can guide task planning, enabling robots to predict and adapt to human actions in real time (9 citations, 2023). Additionally, his work on model predictive control for a soft elbow exosuit significantly reduces interaction torque, enhancing comfort and usability (4 citations, 2023). With a portfolio that spans high-density EMG, brain-computer interfaces, and soft robotics, Tacca is shaping the future of seamless, human-centered automation.
Research Focus
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Top Papers
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