Distributed Adaptive Control for Virtual Cyborgs: A Case Study for Personalized Rehabilitation.

As robotics and artificial intelligence have become greatly advanced, cyborgs are often envisioned as the next step in human evolution. Once only a fictional concept, nowadays, cyborg systems can be used to support people with neurological impairments and enhance their quality of life. Recent technological advances have given rise to numerous novel solutions for neurorehabilitation, in which combining wearable exoskeletons and virtual reality-based exercises has emerged as a promising technique. Nonetheless, there is often a lack of a control architecture that effectively integrates and coordinates the adaptation of different modules within such VR-robotic synergistic rehabilitative systems. In this pilot study, we propose a multi-level adaptive coaching paradigm based on the notion of ‘virtual cyborgs’ and evaluate its core components. By modeling the digitized representations of exoskeleton-assisted human subjects and providing adaptation through a distributed control architecture, we aim to establish a groundwork for personalized interventions that are more accessible than available treatments.