Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

Journal of NeuroEngineering and Rehabilitation, 2019 · DOI: https://doi.org/10.1186/s12984-019-0559-z · Published: June 26, 2019

Assistive Technology Neurorehabilitation Biomechanics

Simple Explanation

This study focuses on developing a human-machine interface (HMI) that enables individuals with neurological impairments to voluntarily control robotic exoskeletons. The HMI uses electromyography (EMG) signals to drive a musculoskeletal model, translating neural signals into exoskeleton movements. The developed HMI was tested on poststroke and incomplete spinal cord injury patients, allowing them to control multiple joints in a multifunctional robotic exoskeleton in real time. This approach aims to promote neuroplasticity and improve motor function recovery. The study demonstrated that increased exoskeleton assistance led to a reduction in muscle activation and mechanical moments required to perform motor tasks, indicating precise synchronization between the device and the patient's residual voluntary muscle contraction.

Study Duration

Not specified

Participants

4 healthy individuals, 1 incomplete SCI patient, and 2 hemiparetic stroke patients

Evidence Level

Not specified

Key Findings

1
Patients with paresis can achieve continuous voluntary control of robotic exoskeletons using the developed EMG-driven musculoskeletal model-based HMI, even with paretic and spastic-like muscle activity.
2
Increased exoskeleton assistance results in a reduction in both the amplitude and variability of muscle activations, as well as a reduction in joint moments required to perform motor tasks.
3
The developed HMI precisely synchronizes device actuation with human muscle contraction, which is especially challenging in populations with paretic and spastic-like muscle activity.

Research Summary

The study introduces a patient-specific computational model of the human musculoskeletal system controlled via EMG-derived neural activations, synthesized into an HMI for voluntary control of robotic exoskeletons. Results demonstrate patients’ control accuracy across various lower-extremity motor tasks, with increased exoskeleton assistance reducing muscle activations and mechanical moments. The findings suggest that the proposed methodology may open new avenues for leveraging residual neuromuscular function in neurologically impaired individuals through symbiotic wearable robots, enabling personalized neurorehabilitation technologies.

Practical Implications

Personalized Neurorehabilitation

The patient-specific model can be used to tailor exoskeleton assistance to individual needs, maximizing motor recovery.

Symbiotic Wearable Robots

The technology enables exoskeletons to dynamically adapt to the patient’s motor capacity across different stages of recovery, operating symbiotically with the human body.

Assessment of Motor Capacity

The HMI could aid clinicians and physiotherapists in assessing patients’ motor capacity and progress over time, providing quantitative data for rehabilitation planning.

Study Limitations

1
The study involved voluntary control of robotic knee and ankle rotations from a seated position, limiting the assessment of more functional tasks such as walking.
2
The effect of noncalibrated models on exoskeleton control was not tested.
3
The quality of model-optimized parameters needs validation against in-vivo experimental values.

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