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About

Vincent Mendez is a leading researcher at the intersection of neural engineering and assistive robotics, dedicated to restoring hand function for upper-limb amputees. His work centers on developing intelligent, intuitive control systems for robotic prosthetic hands, moving beyond the limited on/off commands of current commercial devices. Mendez’s major contributions lie in pioneering shared human-robot proportional control, where his most-cited paper (146 citations) demonstrates a dexterous myoelectric prosthesis that collaborates with the user for more natural manipulation. He has also advanced the field through EMG-driven compliant control for in-hand object manipulation and the application of deep learning with convolutional neural networks for proportional finger control. His comprehensive review, "Current Solutions and Future Trends for Robotic Prosthetic Hands" (107 citations), is a seminal resource for the community. More recently, Mendez has explored hardware-efficient neural decoders and EMG data augmentation using generative adversarial networks to improve grasp classification. His work consistently pushes toward seamless, human-like control, making him a pivotal figure in the next generation of bionic hands.