一种用于肌肉冗余解决的无调优变分框架：具有活动集切换和肌电图验证激活预测的扭矩纤维近端动力学
A Tuning-Free Variational Framework for Muscle Redundancy Resolution: Torque Fiber Proximal Dynamics with Active-Set Switching and EMG-Validated Activation Prediction
浏览论文内容
中文总结 AI 辅助
研究针对肌肉冗余问题，提出扭矩纤维近端动力学（TFPD）框架，激活依特定投影演变，拮抗肌募集自然产生。推导相关条件，经肘部模型验证，与肌电图相关性良好且无需调参，还证明鲁棒性，将神经肌肉协调与多种理论及系统相联系。
中文摘要 AI 辅助
肌肉冗余可被表述为对随时间变化的可行激活凸集的约束选择。我们引入了扭矩纤维近端动力学（TFPD），其中激活作为先前状态在由扭矩等式和生理界限定义的凸多面体上的欧几里得投影而演变。TFPD等同于扫掠过程的后向欧拉离散化以及具有最大单调法锥算子的变分不等式。在该框架下，基于投影的控制假设下，拮抗肌募集作为由几何结构引起的活动集转变的结构结果自然出现，而非强加的成本。我们推导了在一般力臂不对称情况下拮抗肌激活的基于KKT的充分条件，将边界投影、严格互补性和扭矩耦合联系起来。我们使用精确二次规划在三肌肉肘部模型上验证了TFPD，将其与五种经典方法和随机基线进行基准测试，在十名受试者中与肱三头肌肌电图包络的皮尔逊相关系数达到0.68 - 0.73，且无需任何可调成本权重参数。敏感性分析和三维激活轨迹可视化证明了其鲁棒性。TFPD将神经肌肉协调与近端点理论、变分不等式和投影动力系统联系起来。
英文摘要
Muscle redundancy can be formulated as a constrained selection on a time-varying convex set of feasible activations. We introduce Torque Fiber Proximal Dynamics (TFPD), where activation evolves as the Euclidean projection of the previous state onto a convex polytope defined by torque equality and physiological bounds. TFPD is equivalent to a backward-Euler discretization of a sweeping process and a variational inequality with a maximal monotone normal cone operator. Within this framework, antagonist recruitment emerges naturally under a projection-based control hypothesis as a structural consequence of active-set transitions induced by the geometry, not as an imposed cost. We derive sufficient KKT-based conditions for antagonist activation under generic moment-arm asymmetry, linking boundary projection, strict complementarity, and torque coupling. We validate TFPD on a three-muscle elbow model using exact quadratic programming, benchmark it against five classical methods and a random baseline, and achieve a Pearson correlation of 0.68-0.73 with triceps EMG envelopes across ten subjects without any tunable cost-weight parameters. Sensitivity analysis and a three-dimensional activation trajectory visualization demonstrate robustness. TFPD connects neuromuscular coordination to proximal point theory, variational inequalities, and projected dynamical systems.
