论文标题
通过高阶张量分解对肌电控制提取的肌肉协同作用的一致性
Consistency of Muscle Synergies Extracted via Higher-Order Tensor Decomposition Towards Myoelectric Control
论文作者
论文摘要
近年来，肌肉协同作用已被实现以进行比例的肌电控制。使用矩阵分解技术（主要是非负矩阵分解，NMF）提取协同作用，该技术需要鉴定与任务或运动的协同作用。另外，NMF方法仅具有2度自由度（DOF）的任务维度才能可行。在这里，探索了高阶张量模型在肌电控制中的潜在用途。我们评估限制的塔克张量分解的能力，当任务维度提高到3-DOF时估计一致的协同作用。比较了从1和3 DOF的3阶张量提取的协同作用。结果表明，通过约束的塔克分解提取的肌肉协同作用与任务维度的增加一致。因此，这些结果支持基于张量分解的比例3型肌电控制的考虑。
In recent years, muscle synergies have been pro-posed for proportional myoelectric control. Synergies were extracted using matrix factorisation techniques (mainly non-negative matrix factorisation, NMF), which requires identification of synergies to tasks or movements. In addition, NMF methods were viable only with a task dimension of 2 degrees of freedoms(DoFs). Here, the potential use of a higher-order tensor model for myoelectric control is explored. We assess the ability of a constrained Tucker tensor decomposition to estimate consistent synergies when the task dimensionality is increased up to 3-DoFs. Synergies extracted from 3rd-order tensor of 1 and 3 DoFs were compared. Results showed that muscle synergies extracted via constrained Tucker decomposition were consistent with the increase of task-dimension. Hence, these results support the consideration of proportional 3-DoF myoelectric control based on tensor decompositions.
