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一种能够模拟手部和腕部功能任务的肌肉骨骼模型。

A Musculoskeletal Model of the Hand and Wrist Capable of Simulating Functional Tasks.

出版信息

IEEE Trans Biomed Eng. 2023 May;70(5):1424-1435. doi: 10.1109/TBME.2022.3217722. Epub 2023 Apr 20.

Abstract

OBJECTIVE

The purpose of this work was to develop an open-source musculoskeletal model of the hand and wrist and to evaluate its performance during simulations of functional tasks.

METHODS

The current model was developed by adapting and expanding upon existing models. An optimal control theory framework that combines forward-dynamics simulations with a simulated-annealing optimization was used to simulate maximum grip and pinch force. Active and passive hand opening were simulated to evaluate coordinated kinematic hand movements.

RESULTS

The model's maximum grip force production matched experimental measures of grip force, force distribution amongst the digits, and displayed sensitivity to wrist flexion. Simulated lateral pinch strength replicated in vivo palmar pinch strength data. Additionally, predicted activations for 7 of 8 muscles fell within variability of EMG data during palmar pinch. The active and passive hand opening simulations predicted reasonable activations and demonstrated passive motion mimicking tenodesis, respectively.

CONCLUSION

This work advances simulation capabilities of hand and wrist models and provides a foundation for future work to build upon.

SIGNIFICANCE

This is the first open-source musculoskeletal model of the hand and wrist to be implemented during both functional kinetic and kinematic tasks. We provide a novel simulation framework to predict maximal grip and pinch force which can be used to evaluate how potential surgical and rehabilitation interventions influence these functional outcomes while requiring minimal experimental data.

摘要

目的

本研究旨在开发一种开源的手部和腕部肌肉骨骼模型,并评估其在功能任务模拟中的性能。

方法

当前模型是通过改编和扩展现有的模型开发的。采用结合正向动力学模拟和模拟退火优化的最优控制理论框架,模拟最大握力和捏力。模拟主动和被动手部张开,以评估协调的手部运动。

结果

模型的最大握力生成与握力的实验测量、手指间的力分布以及对腕关节屈曲的敏感性相匹配。模拟的横向捏力复制了体内掌侧捏力数据。此外,在手掌捏合期间,预测的 8 块肌肉中的 7 块肌肉的激活与肌电图数据的变异性一致。主动和被动手部张开模拟分别预测了合理的激活并模拟了肌腱切除术的被动运动。

结论

这项工作推进了手部和腕部模型的仿真能力,并为未来的工作提供了基础。

意义

这是第一个在功能动力学和运动学任务中实施的开源手部和腕部肌肉骨骼模型。我们提供了一种新的模拟框架来预测最大握力和捏力,可用于评估潜在的手术和康复干预如何影响这些功能结果,同时只需要最少的实验数据。

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