Neuromusculoskeletal Modeling-Based Prostheses for Recovery After Spinal Cord Injury

Front. Neurorobot., 2019 · DOI: 10.3389/fnbot.2019.00097 · Published: December 2, 2019

Spinal Cord Injury Neurorehabilitation Biomechanics

Simple Explanation

Spinal cord injuries interrupt connections between the brain, spinal cord, and muscles, hindering motor commands and sensory signals. Combining techniques like exoskeletons and electrical stimulation can help restore movement, but current designs often oversimplify the human body's complexity. Personalized neuromusculoskeletal models can enhance neurorehabilitation by interfacing with electromechanical devices to improve motor function and track progress.

Study Duration

Not specified

Participants

Not specified

Evidence Level

Level: Not specified, Study type: Narrative Review

Key Findings

1
Neuromusculoskeletal models can optimize muscle stimulation patterns, track functional improvement, monitor safety, and provide augmented feedback during exercise-based rehabilitation.
2
Combining multiple assistive devices, such as BCI with FES or robotics, can maximize functional outcomes for individuals with SCI.
3
Real-time NMS modeling enables integration of assistive devices by acting as a digital twin, interpreting between the human and the machine and monitoring internal tissue state.

Research Summary

This review discusses the potential of integrating real-time neuromusculoskeletal (NMS) models with assistive devices for spinal cord injury (SCI) rehabilitation to promote neural restoration. The utility of NMS models for optimizing muscle stimulation patterns, tracking functional improvement, monitoring safety, and providing augmented feedback during exercise-based rehabilitation are discussed. Challenges like BCI robustness and NMS model personalization need addressing. However, NMS modeling-based neuromechanical prostheses hold potential to improve assistive technologies and neural recovery after SCI.

Practical Implications

Personalized Therapy

NMS models can be used to develop personalized therapies that reduce clinician guesswork and automatically adapt to the patient's recovering muscle activation patterns.

Enhanced Rehabilitation Outcomes

By integrating multiple assistive devices with NMS models, rehabilitation outcomes can be greatly enhanced through physics-based sensor fusion and improved human-machine interaction.

Safety Monitoring

NMS models, combined with finite element analysis, can provide instantaneous estimates of tissue stresses and strains, ensuring musculoskeletal tissues are loaded within safe limits during therapy.

Study Limitations

1
Current BCI approaches based on motor imagery are not sufficiently robust and require retraining neural decoders each session.
2
Personalizing NMS models involves time-consuming semi-automatic processing of medical imaging data.
3
Effective dosage of exercise, feedback modality and pharmacological agents need to be understood through clinical trials.

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