Advances in robotics are leading major changes in health care, physiotherapy, and rehabilitation. As we bring robots and other mechatronic devices in such a close contact with (or attachment to) humans, one of major challenges we face is how we should plan or “automate” the reactions to humans for different levels of assistance. This process also entails our in-depth understanding of neuroscientific principles that underline basic human motor behaviors. This project utilizes a bimanual assistive robotic platform to address these issues by bringing together experts in mechatronics, control theory, biomedical engineering, neuroscience and neuro-rehabilitation. Going beyond the boundaries of conventional disciplines, this research is aimed at 1) understanding computational mechanisms behind human sensorimotor learning, 2) realizing biologically-inspired robotic manipulation with human-like dexterity, and 3) developing intelligent control strategies for robotic rehabilitation therapies.
This research was planned and being conducted in collaboration with experts of diverse backgrounds including Profs. Ewa Niechwiej-Szwedo and Michael Barnett-Cowan in Kinesionology at the Faculty of Health Sciences, and Profs. James Tung, Arash Arami and Baris Fidan in the areas of Biomechanics and Mechatronics Engineering.
Related publication
- M. Nazarahari, Ajami, S. , Jeon, S. , and Arami, A. , “Visual Feedback Decoding During Bimanual Circle Drawing”, Journal of Neurophysiology, vol. 130, no. 5, 2023.
- M. Nouredanesh, Frazer, M., Tung, J., Jeon, S., and Arami, A., “Effect of Visual Information on Dominant and Non-dominant Hands during a Bi-manual Drawing in a Robotic Platform”, in IEEE-RAS-EMBS International Conference on Rehabilitation Robotics (ICORR), 2019, pp. 1221-1226.