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About

Vincent Hernandez is a researcher at the intersection of robotics, biomechanics, and ergonomics, whose work focuses on modeling and predicting human upper-limb force capabilities. His primary research areas include robotic-assisted rehabilitation, digital human modeling, and telepresence robotics. Hernandez’s major contributions center on applying robotic models—such as the force ellipsoid and force polytope—to evaluate human force generation, as demonstrated in his most-cited paper, “Human upper-limb force capacities evaluation with robotic models for ergonomic applications: effect of elbow flexion” (2015, 11 citations). He has also pioneered the use of artificial neural networks combined with musculoskeletal models to predict the Force Feasible Set (FFS), a tool with significant potential for refining rehabilitation programs and enhancing ergonomic design (2018, 10 citations). Additionally, Hernandez has explored telepresence robots, developing systems that convey gesture information using force data (2020, 2 citations). While his citation counts are modest, his work bridges engineering and human physiology, offering practical tools for improving assistive technologies and workplace ergonomics. Hernandez’s innovative integration of robotic indices into biomechanical assessment marks him as a thoughtful contributor to human-robot interaction and rehabilitation engineering.