Neuromusculoskeletal Modelling-based Prostheses for Recovery after Spinal Cord Injury
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Pizzolato, Claudio
Saxby, david
Lloyd, david
Diamond, laura
Barrett, rod
Teng, Yang
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Abstract
Concurrent stimulation and reinforcement of motor and sensory pathways has been proposed as an effective approach to restoring function after developmental or acquired neurotrauma. This can be achieved by applying multimodal rehabilitation regimens, such as thought-controlled exoskeletons or epidural electrical stimulation to recover motor pattern generation in individuals with spinal cord injury (SCI). However, the human neuromusculoskeletal (NMS) system has often been oversimplified in designing rehabilitative and assistive devices. As a result, the neuromechanics of the muscles is seldom considered when modelling the relationship between electrical stimulation, mechanical assistance from exoskeletons, and final joint movement. A powerful way to enhance current neurorehabilitation is to develop the next generation prostheses incorporating personalised NMS models of patients. This strategy will enable an individual voluntary interfacing with multiple electromechanical rehabilitation devices targeting key afferent and efferent systems for functional improvement. This narrative review discusses how real-time NMS models can be integrated with finite element of musculoskeletal tissues and interface multiple assistive and robotic devices with individuals with SCI to promote unmatched levels of neural restoration. In particular, the utility of NMS models for optimising muscle stimulation patterns, tracking functional improvement, monitoring safety and providing augmented feedback during exercise-based rehabilitation are discussed.
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Frontiers in Neurorobotics
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Artificial intelligence
Biomedical engineering
Medical biotechnology
Clinical sciences
Neurosciences
Engineering
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Palipana, D; Pizzolato, C; Saxby, D; Lloyd, D; Diamond, L; Barrett, R; Teng, Y, Neuromusculoskeletal Modelling-based Prostheses for Recovery after Spinal Cord Injury, Frontiers in Neurorobotics, 2019