In recent years, some scientific papers showed that the combination of visual and electromyography data can strongly extend the capabilities of dexterous prostheses. With MEGANE PRO, we aim to bring the research in this field to its next step, i.e. to better understand the neurologic and neurocognitive effects of amputation on the persons and to strongly improve robotic prosthesis control possibilities by hand amputated subjects.
MEGANE PRO will be the first multimodal database from intact and hand amputated subjects mixing several different data sources to improve patient rehabilitation and neuro-cognitive understanding. The project includes also the application of machine learning algorithms on multimodal data in order to perform movement classification for prosthesis control. The combination of multimodal data is expected to strongly improve the movement classification accuracy, and therefore the concrete capabilities of hand prosthetics.
The project is expected to improve:
- The knowledge in the neuro-cognitive field by studying differences between intact and hand amputated subjects
- The state of the art in hand prosthetics
- The clinical outcome of the patients (e.g., by better understanding the individual phantom limb phenomenology)