Autor: |
Tony Shu, Shan Shan Huang, Christopher Shallal, Hugh M. Herr |
Jazyk: |
angličtina |
Rok vydání: |
2021 |
Předmět: |
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Zdroj: |
Journal of NeuroEngineering and Rehabilitation, Vol 18, Iss 1, Pp 1-17 (2021) |
Druh dokumentu: |
article |
ISSN: |
1743-0003 |
DOI: |
10.1186/s12984-021-00829-z |
Popis: |
Abstract Background Neuroprosthetic devices controlled by persons with standard limb amputation often lack the dexterity of the physiological limb due to limitations of both the user’s ability to output accurate control signals and the control system’s ability to formulate dynamic trajectories from those signals. To restore full limb functionality to persons with amputation, it is necessary to first deduce and quantify the motor performance of the missing limbs, then meet these performance requirements through direct, volitional control of neuroprosthetic devices. Methods We develop a neuromuscular modeling and optimization paradigm for the agonist-antagonist myoneural interface, a novel tissue architecture and neural interface for the control of myoelectric prostheses, that enables it to generate virtual joint trajectories coordinated with an intact biological joint at full physiologically-relevant movement bandwidth. In this investigation, a baseline of performance is first established in a population of non-amputee control subjects ( $$n = 8$$ n = 8 ). Then, a neuromuscular modeling and optimization technique is advanced that allows unilateral AMI amputation subjects ( $$n = 5$$ n = 5 ) and standard amputation subjects ( $$n = 4$$ n = 4 ) to generate virtual subtalar prosthetic joint kinematics using measured surface electromyography (sEMG) signals generated by musculature within the affected leg residuum. Results Using their optimized neuromuscular subtalar models under blindfolded conditions with only proprioceptive feedback, AMI amputation subjects demonstrate bilateral subtalar coordination accuracy not significantly different from that of the non-amputee control group (Kolmogorov-Smirnov test, $$P \ge 0.052$$ P ≥ 0.052 ) while standard amputation subjects demonstrate significantly poorer performance (Kolmogorov-Smirnov test, $$P < 0.001$$ P < 0.001 ). Conclusions These results suggest that the absence of an intact biological joint does not necessarily remove the ability to produce neurophysical signals with sufficient information to reconstruct physiological movements. Further, the seamless manner in which virtual and intact biological joints are shown to coordinate reinforces the theory that desired movement trajectories are mentally formulated in an abstract task space which does not depend on physical limb configurations. |
Databáze: |
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