Antagonistic Feedback Control of Muscle Length Changes for Efficient Involuntary Posture Stabilization.

IF 3.4 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY Biomimetics Pub Date : 2024-10-11 DOI:10.3390/biomimetics9100618
Masami Iwamoto, Noritoshi Atsumi, Daichi Kato
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Abstract

Simultaneous and cooperative muscle activation results in involuntary posture stabilization in vertebrates. However, the mechanism through which more muscles than joints contribute to this stabilization remains unclear. We developed a computational human body model with 949 muscle action lines and 22 joints and examined muscle activation patterns for stabilizing right upper or lower extremity motions at a neutral body posture (NBP) under gravity using actor-critic reinforcement learning (ACRL). Two feedback control models (FCM), muscle length change (FCM-ML) and joint angle differences, were applied to ACRL with a normalized Gaussian network (ACRL-NGN) or deep deterministic policy gradient. Our findings indicate that among the six control methods, ACRL-NGN with FCM-ML, utilizing solely antagonistic feedback control of muscle length change without relying on synergy pattern control or categorizing muscles as flexors, extensors, agonists, or synergists, achieved the most efficient involuntary NBP stabilization. This finding suggests that vertebrate muscles are fundamentally controlled without categorization of muscles for targeted joint motion and are involuntarily controlled to achieve the NBP, which is the most comfortable posture under gravity. Thus, ACRL-NGN with FCM-ML is suitable for controlling humanoid muscles and enables the development of a comfortable seat design.

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肌肉长度变化的拮抗反馈控制,实现高效的非自主姿势稳定。
在脊椎动物中,肌肉的同步合作激活会导致不自主的姿势稳定。然而,肌肉比关节更能促进这种稳定的机制仍不清楚。我们开发了一个具有 949 条肌肉动作线和 22 个关节的计算人体模型,并利用演员批判强化学习(ACRL)研究了在重力作用下稳定中性身体姿势(NBP)的右上肢或下肢运动的肌肉激活模式。两种反馈控制模型(FCM),即肌肉长度变化(FCM-ML)和关节角度差异,被应用于带有归一化高斯网络(ACRL-NGN)或深度确定性策略梯度的 ACRL。我们的研究结果表明,在六种控制方法中,ACRL-NGN 与 FCM-ML,仅利用肌肉长度变化的拮抗反馈控制,而不依赖协同模式控制或将肌肉分为屈肌、伸肌、激动肌或协同肌,实现了最有效的非自主 NBP 稳定。这一研究结果表明,脊椎动物的肌肉从根本上说是在不对肌肉进行分类的情况下进行控制,以实现有针对性的关节运动,并通过非自主控制实现 NBP,即重力作用下最舒适的姿势。因此,带有 FCM-ML 的 ACRL-NGN 适用于控制类人肌肉,并能开发出舒适的座椅设计。
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来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
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