用基于深度强化学习的控制器预测理想化外骨骼辅助下的坐立运动

IF 2.6 2区 工程技术 Q2 MECHANICS
Neethan Ratnakumar, Kübra Akbaş, Rachel Jones, Zihang You, Xianlian Zhou
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引用次数: 0

摘要

保持从坐到站的转换能力对于保持老年人和肌肉骨骼疾病患者的功能独立性和整体活动能力至关重要。下肢外骨骼有可能在支持这一关键能力方面发挥重要作用。本研究开发了一种基于深度强化学习(DRL)的坐立(STS)控制器,用于研究外骨骼辅助和无辅助情况下的坐立生物力学。研究探讨了三种不同的情况:1)髋关节辅助(H-Exo);2)膝关节辅助(K-Exo);3)髋膝关节辅助(H+K-Exo)。通过使用通用的肌肉骨骼模型,在这些情况下生成的 STS 关节轨迹与无辅助实验观察结果一致。我们观察到在 STS 循环过程中肌肉活化程度大幅降低,与无辅助 STS 情景相比,在 H+K-Exo 辅助下,主要髋关节伸肌(臀大肌)和主要膝关节伸肌(vasti)的平均活化程度分别降低了 68.63% 和 73.23%。不过,在 H-Exo 和 K-Exo 情景下,腘绳肌和腓肠肌的肌肉活化程度意外增加,这可能表明这是一种稳定性补偿机制。相比之下,H+K-Exo 综合辅助则显示出这些肌肉的激活明显减少。这些发现凸显了坐立辅助的潜力,尤其是在髋膝外骨骼组合情况下,并为开发基于 DRL 的强大辅助设备控制器提供了宝贵的见解,以改善功能结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Predicting sit-to-stand motions with a deep reinforcement learning based controller under idealized exoskeleton assistance

Predicting sit-to-stand motions with a deep reinforcement learning based controller under idealized exoskeleton assistance

Maintaining the capacity for sit-to-stand transitions is paramount for preserving functional independence and overall mobility in older adults and individuals with musculoskeletal conditions. Lower limb exoskeletons have the potential to play a significant role in supporting this crucial ability. In this investigation, a deep reinforcement learning (DRL) based sit-to-stand (STS) controller is developed to study the biomechanics of STS under both exoskeleton assisted and unassisted scenarios. Three distinct conditions are explored: 1) Hip joint assistance (H-Exo), 2) Knee joint assistance (K-Exo), and 3) Hip-knee joint assistance (H+K-Exo). By utilizing a generic musculoskeletal model, the STS joint trajectories generated under these scenarios align with unassisted experimental observations. We observe substantial reductions in muscle activations during the STS cycle, with an average decrease of 68.63% and 73.23% in the primary hip extensor (gluteus maximus) and primary knee extensor (vasti) muscle activations, respectively, under H+K-Exo assistance compared to the unassisted STS scenario. However, the H-Exo and K-Exo scenarios reveal unexpected increases in muscle activations in the hamstring and gastrocnemius muscles, potentially indicating a compensatory mechanism for stability. In contrast, the combined H+K-Exo assistance demonstrates a noticeable reduction in the activation of these muscles. These findings underscore the potential of sit-to-stand assistance, particularly in the combined hip-knee exoskeleton scenario, and contribute valuable insights for the development of robust DRL-based controllers for assistive devices to improve functional outcomes.

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来源期刊
CiteScore
6.00
自引率
17.60%
发文量
46
审稿时长
12 months
期刊介绍: The journal Multibody System Dynamics treats theoretical and computational methods in rigid and flexible multibody systems, their application, and the experimental procedures used to validate the theoretical foundations. The research reported addresses computational and experimental aspects and their application to classical and emerging fields in science and technology. Both development and application aspects of multibody dynamics are relevant, in particular in the fields of control, optimization, real-time simulation, parallel computation, workspace and path planning, reliability, and durability. The journal also publishes articles covering application fields such as vehicle dynamics, aerospace technology, robotics and mechatronics, machine dynamics, crashworthiness, biomechanics, artificial intelligence, and system identification if they involve or contribute to the field of Multibody System Dynamics.
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