Modelling the neuromusculoskeletal system across spatiotemporal scales for a new paradigm of human-machine motor interaction

Objective

Neurological injuries such as stroke leave millions of people disabled worldwide every year. For these individuals motor recovery is often suboptimal. The impact of current neurorehabilitation machines is hampered by limited knowledge of their physical interaction with the human. As we move, our body adapts positively to optimal stimuli; motor improvement after stoke is promoted via physical training with an appropriate afferent input to the nervous system and mechanical loads to muscles. Loss of appropriate stimuli leads to motor dysfunction.
Motor recovery requires positive neuromuscular adaptations to be steered over time. If neuro-modulative and orthotic machines could be controlled to generate optimal stimuli to the neuromuscular system, a new era in neurorehabilitation would begin.
This project creates multi-scale models of human-machine interaction for radically new closed-loop control paradigms. We will combine biosignal recording and numerical modeling to decode the cellular activity of motor neurons in the spinal cord with resulting musculoskeletal forces at a resolution not considered before. This will enable breakthroughs for tracking the spinal-musculoskeletal system across spatiotemporal scales: short-to-long term adaptation from cellular to organ scales. We will use these concepts to design new machine control schemes. With a focus on spinal cord electrical stimulation and mechatronic exosuits, we will demonstrate how motor dysfunction is repaired by inducing optimal changes in neuromuscular targets. The innovative aspect is that of gaining control of the stimuli that govern neuromuscular function over time. This will enable machines to co-adapt with the body; an achievement that will disrupt the development of man-machine interfaces from neuroprostheses, to robotic limbs, to exosuits.
INTERACT will answer fundamental questions in movement neuromechanics via novel principles of human-machine interaction with broad impact on bioengineering and robotics

Field of science

• /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/robotics

Programme(s)

• H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)

Topic(s)

• ERC-2018-STG - ERC Starting Grant

Call for proposal

ERC-2018-STG
See other projects for this call

Funding Scheme

Host institution

Beneficiaries (1)