ABSTRACT
This paper presents an upper limb exoskeleton that allows cognitive (through electromyography signals) and physical user interaction (through load cells sensors) for passive and active exercises that can activate neuroplasticity in the rehabilitation process of people who suffer from a neurological injury. For the exoskeleton to be easily accepted by patients who suffer from a neurological injury, we used the ISO9241-210:2010 as a methodology design process. As the first steps of the design process, design requirements were collected from previous usability tests and literature. Then, as a second step, a technological solution is proposed, and as a third step, the system was evaluated through performance and user testing. As part of the technological solution and to allow patient participation during the rehabilitation process, we have proposed a hybrid admittance control whose input is load cell or electromyography signals. The hybrid admittance control is intended for active therapy exercises, is easily implemented, and does not need musculoskeletal modeling to work. Furthermore, electromyography signals classification models and features were evaluated to identify the best settings for the cognitive human-robot interaction.
ABSTRACT
Virtual reality (VR) in neurorehabilitation allows to reduce patient's risk and allows him to learn on a faster way. Up to now VR has been used in patients with Parkinson disease (PD) as a research tool and none of the developed systems are used in clinical practice. The goal of this project is to develop a VR-based system for gait therapy, and gait research of patients with PD designed based on published evidence. The developed system uses a digital camera to measure spatiotemporal gait parameters. The software was developed in C#, using Open-Source libraries that facilitates VR programming. The system has potential uses in clinical and research settings.
