Papers
2
Total Citations
14
H-Index
2
About
John Wandeto is a pioneering researcher at the intersection of robotics, neuroscience, and surgical skill assessment. His work centers on somatosensory cognition and the biomechanics of manual dexterity, using innovative spatiotemporal modeling to decode how grip forces reveal proficiency in complex tasks. In his landmark 2023 study, “Spatiotemporal Modeling of Grip Forces Captures Proficiency in Manual Robot Control” (10 citations), Wandeto introduced novel technologies for monitoring grip forces during non-standard hand and finger movements, offering unprecedented insights into the neural basis of object manipulation. This work has profound implications for advancing human-robot interaction and rehabilitation. His 2021 paper, “Surgical task expertise detected by a self-organizing neural network map” (4 citations), further demonstrates his impact by developing benchmark criteria that distinguish expert surgeons from novices through grip force variability in bimanual simulator tasks. By applying self-organizing neural networks to robotic control devices for endoscopic surgery, Wandeto has created objective metrics for surgical training and certification. His research bridges cognitive science and practical robotics, promising to transform how we train surgeons and design intuitive robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Surgical task expertise detected by a self-organizing neural network map4 citations · 2021