Periodic Reporting for period 3 - INTERACT (Modelling the neuromusculoskeletal system across spatiotemporal scales for a new paradigm of human-machine motor interaction)
Période du rapport: 2022-01-01 au 2023-06-30
Robotic exoskeletons and neuromodulation devices have long been designed with the goal of enhancing or restoring human movement. However, despite advances in surgical procedures, biocompatible implants, and mechatronics, current solutions have had only modest results in healthy and neurologically impaired individuals. A central element hampering progress is the difficulty of predicting how the human body responds to neuro-robotic interventions.
Neuro-robotic technologies expose biological targets in the neuromuscular system to electrical and mechanical stimuli. For instance, mechanical strains and loads delivered via robotic exoskeletons to skeletal muscles may lead to changes in fascicle kinematics. Similarly, electrical currents delivered to the spine via electrical stimulators may alter excitability in spinal neurons responsible for the control of skeletal muscle force (e.g. alpha motor neurons). Whether or not these neuromuscular alterations improve the way an individual moves cannot be predicted before-hand. If we could predict how a person’s neuromuscular system responds to neuro-robotic interventions, and steer such neuromuscular response to enhance movement capacity, then a new era in closed-loop rehabilitation robotics would begin.
This represents a major challenge, which if address, would lead to a paradigm shift in neurorehabilitation technologies, with profound repercussions in broad scientific domains spanning from movement neuromechanics to robotics. Addressing this challenge would also have tremendous socio-economic impact, e.g. neurological injuries such as spinal cord injury or stroke leave every year 5 million people disabled worldwide. For these individuals, recovery is often suboptimal leading to permanent impairment in increasingly large portions of the population.
INTERACT will create radically new digital models of the composite human neuromuscular system that can predict how the human body responds over time with levels of precision not achieved before. This represents a new class of human digital twins (e.g. a digital copy of a person’s neuromuscular system), which can be used to establish radically new closed-loop control paradigms. This will lead to a class of neuro-robotic technologies that that interact with the body based on feedback from the neuromuscular system, thereby ‘closing-the-loop’ with human biology.
Neuro-robotic technologies expose biological targets in the neuromuscular system to electrical and mechanical stimuli. For instance, mechanical strains and loads delivered via robotic exoskeletons to skeletal muscles may lead to changes in fascicle kinematics. Similarly, electrical currents delivered to the spine via electrical stimulators may alter excitability in spinal neurons responsible for the control of skeletal muscle force (e.g. alpha motor neurons). Whether or not these neuromuscular alterations improve the way an individual moves cannot be predicted before-hand. If we could predict how a person’s neuromuscular system responds to neuro-robotic interventions, and steer such neuromuscular response to enhance movement capacity, then a new era in closed-loop rehabilitation robotics would begin.
This represents a major challenge, which if address, would lead to a paradigm shift in neurorehabilitation technologies, with profound repercussions in broad scientific domains spanning from movement neuromechanics to robotics. Addressing this challenge would also have tremendous socio-economic impact, e.g. neurological injuries such as spinal cord injury or stroke leave every year 5 million people disabled worldwide. For these individuals, recovery is often suboptimal leading to permanent impairment in increasingly large portions of the population.
INTERACT will create radically new digital models of the composite human neuromuscular system that can predict how the human body responds over time with levels of precision not achieved before. This represents a new class of human digital twins (e.g. a digital copy of a person’s neuromuscular system), which can be used to establish radically new closed-loop control paradigms. This will lead to a class of neuro-robotic technologies that that interact with the body based on feedback from the neuromuscular system, thereby ‘closing-the-loop’ with human biology.
The INTERACT team established novel methodologies for creating digital copies of a person’s neuromuscular system. The first part of the project focused on modelling the behavior of a type of neural cells located in the spinal cord that are responsible for the generation of movement, i.e. the α-motor neuron. The team modelled how α-motor neurons fire and innervate with skeletal muscles. A major challenge was the identification of anatomical and functional properties from large sets of α-motor neurons in human subjects and in a non-invasive way (i.e. these studies are typically done in animal preparations using invasive techniques). To address this challenge, the team developed new non-invasive and clinically-viable system identification methods that allowed creating digital versions of a person’s spinal neurons (e.g. in silico neuronal copies) that behaved similarly to their biological counterparts, when tested during simple leg movement exercises involving healthy individuals.
This methodology has been employed to advance knowledge on how α-motor neurons respond to electrical stimulation delivered transcutaneously in a small group of spinal cord injury individuals. These results are now leading to new concepts of human-machine interfacing. In this context, the INTERACT team recently showed to be able to decode the activity of alpha motor neurons in spinal cord injury patients receiving transcutaneous spinal cord stimulation. Our results showed that our motor neuron interface was sensitive enough to detect changes in the common synaptic input received by motor neurons. These results may enable the development of closed-loop controlled neuro-modulative technologies for the modulation of spinal cord excitability.
The INTERACT team also created digital copies of skeletal muscles. A new numerical model was proposed for the estimation of musculoskeletal stiffness during dynamic movements, with a focus on the human leg. State of the art approaches largely rely on biological joint perturbation techniques, which alter musculoskeletal function and prevent measuring stiffness in natural (unperturbed) conditions. INTERACT created a new approach that is not based on joint-perturbation, but rather decodes stiffness from muscle electromyography recordings and leg kinematic data with direct validation with single muscle and tendon resolution. This opens to new views into how the nervous system controls body motions in natural conditions with large implications for neurorehabilitation and robotic control.
The INTERACT digital modelling technology was employed for the control of wearable robotic exoskeletons. The team conducted a series of studies that proved a crucial concept, i.e. whether neurologically injured patients could regain control of their paretic legs using exoskeletons controlled via the patient’s digital twin. Key results showed it was possible to create digital twins for both spinal cord injury and post-stroke individuals. Digital twins were used to establish a new patient-exoskeleton interface, which enabled patients to gain volitional control of exoskeletons and move again their paretic legs in ways that were not otherwise possible.
This methodology has been employed to advance knowledge on how α-motor neurons respond to electrical stimulation delivered transcutaneously in a small group of spinal cord injury individuals. These results are now leading to new concepts of human-machine interfacing. In this context, the INTERACT team recently showed to be able to decode the activity of alpha motor neurons in spinal cord injury patients receiving transcutaneous spinal cord stimulation. Our results showed that our motor neuron interface was sensitive enough to detect changes in the common synaptic input received by motor neurons. These results may enable the development of closed-loop controlled neuro-modulative technologies for the modulation of spinal cord excitability.
The INTERACT team also created digital copies of skeletal muscles. A new numerical model was proposed for the estimation of musculoskeletal stiffness during dynamic movements, with a focus on the human leg. State of the art approaches largely rely on biological joint perturbation techniques, which alter musculoskeletal function and prevent measuring stiffness in natural (unperturbed) conditions. INTERACT created a new approach that is not based on joint-perturbation, but rather decodes stiffness from muscle electromyography recordings and leg kinematic data with direct validation with single muscle and tendon resolution. This opens to new views into how the nervous system controls body motions in natural conditions with large implications for neurorehabilitation and robotic control.
The INTERACT digital modelling technology was employed for the control of wearable robotic exoskeletons. The team conducted a series of studies that proved a crucial concept, i.e. whether neurologically injured patients could regain control of their paretic legs using exoskeletons controlled via the patient’s digital twin. Key results showed it was possible to create digital twins for both spinal cord injury and post-stroke individuals. Digital twins were used to establish a new patient-exoskeleton interface, which enabled patients to gain volitional control of exoskeletons and move again their paretic legs in ways that were not otherwise possible.
Current neuro-robotic technologies do not interact directly with biological tissues in the neuromuscular system. That is, they do not take into account how biological targets (e.g. joints, tendons, muscles, neurons) react to robot-induced mechanical or electrical stimuli. This is a major element hampering progress in human-robot interaction for movement enhancement or restoration.
INTERACT proposes a complete re-examination of how neuro-robotic technologies are controlled for optimal interaction with the human body. The project proposes a new theoretical, computational and experimental framework for “closing-the-loop” between wearable technology and human biology, thereby shifting the paradigm in current neuro-robotic control theories. Through this framework INTERACT will lead to a new class of neuro-robotic systems that will deliver coordinated electro-mechanical stimuli to alter, in a controlled way, neuromuscular function from cellular to organ scales.
The impact that this will have on human health is enormous. INTERACT will open new avenues for preserving human tissue integrity throughout highly dynamic tasks. It will enable detecting disruptive neuro-muscular alterations ahead of time and correcting for them, thus preventing for the onset of future injury or degenerative disorders, i.e. osteoarthritis. It will enable tuning the human for optimal motor performance. Through this project, the INTERACT team will open a new research line in movement neuro-mechanics on systems with interacting biological and artificial components, with broad implications for neural-engineering and robotics. This will disrupt human-robot interaction technologies at a fundamental level in any of its applicative domains: from neuromodulation to neuroprosthetics, from robotic limbs to mechatronic exoskeletons and exosuits.
INTERACT proposes a complete re-examination of how neuro-robotic technologies are controlled for optimal interaction with the human body. The project proposes a new theoretical, computational and experimental framework for “closing-the-loop” between wearable technology and human biology, thereby shifting the paradigm in current neuro-robotic control theories. Through this framework INTERACT will lead to a new class of neuro-robotic systems that will deliver coordinated electro-mechanical stimuli to alter, in a controlled way, neuromuscular function from cellular to organ scales.
The impact that this will have on human health is enormous. INTERACT will open new avenues for preserving human tissue integrity throughout highly dynamic tasks. It will enable detecting disruptive neuro-muscular alterations ahead of time and correcting for them, thus preventing for the onset of future injury or degenerative disorders, i.e. osteoarthritis. It will enable tuning the human for optimal motor performance. Through this project, the INTERACT team will open a new research line in movement neuro-mechanics on systems with interacting biological and artificial components, with broad implications for neural-engineering and robotics. This will disrupt human-robot interaction technologies at a fundamental level in any of its applicative domains: from neuromodulation to neuroprosthetics, from robotic limbs to mechatronic exoskeletons and exosuits.