Context-sensitive neural-controlled hand-exoskeleton for restoration of everyday-capability and autonomy after brain and spinal cord injuries
The development of robotic systems that interacts with the human nervous system, promise to improve the autonomy, quality of life, and capability of people with disabilities. Brain-Computer Interfaces (BCI) can be used to translate the electrical brain activity into control signals of a robotic exoskeleton. Therefore, it is possible to restore grasping movements of a paralyzed hand by interpreting the neural correlates of the movement. For lack of signal quality, BCI systems based on non-invasive methods, e.g. electroencephalography (EEG), can only be used limited in everyday situations.
In the project CONSENS-NHE we develope a non-invasive and everyday suitable neural-controlled hand-exoskeleton, targeting the compensation of a paralyzed hand, as it can occur after strokes or spinal cord injuries. Within the project the latest methods of machine learning, optical object-recognition, movement analysis, and biological inspired design for robotic systems are combined with neurorehabilitative research. The system will allow people with hand paralysis to grasp and manipulate different objects of everyday life. For direct control of the hand-exoskeleton, the grasping intention is identified based on neural signals measured on the scalp using EEG.
As part of this project, we develope a system for the neural control of the exoskeleton. This includes:
- Implementation of a user-friendly and intuitive graphical interface on a mobile device to use the neural control and the exoskeleton
- Unsupervised auto-calibration of the BCI for an application in rehabilitative and everyday scenarios
- Adaptive classification methods for cross-session and cross-subject classification
- Development of filter techniques for reliable classification of grasping movement based on EEG signals
- Department of Applied Neurotechnology (Tübingen)
- Department of Cognitive Neurologie (Tübingen)
- Fraunhofer Institute for Manufacturing Engineering and Automation (Stuttgart)
- Institute for Modelling and Simulation of Biomechanical Systems (Stuttgart)
- Department of Cognitive Systems (Reutlingen)
Participating Team Members