A Method for Locomotion Mode Identification Using Muscle Synergies
A Method for Locomotion Mode Identification Using Muscle Synergies
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DOI：
10.1109/tnsre.2016.2585962
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发表时间：
2017-06-01
影响因子：
4.9
通讯作者：
Wright, Andrew B.
中科院分区：
文献类型：
--
作者：
Afzal, Taimoor;Iqbal, Kamran;Wright, Andrew B.
主动下肢经股假肢使截肢者能够执行不同的运动模式，如行走、上楼梯、下楼梯、坡道上升和坡道下降。为了实现无缝模式转换，这些设备要么依赖于来自截肢者残肢的神经信息，要么依赖于附着在假肢上的传感器来识别预期的运动模式，或者两者兼而有之。我们提出了一种基于肌电信号肌肉协同作用框架的运动模式分类方法。关键时刻的神经信息（例如，脚跟接触和脚趾离地）被解码用于此目的。采用非负矩阵分解方法从肌肉特征矩阵中提取肌肉协同效应。使用非负最小二乘法进行神经命令的估计。将肌肉协同方法与线性判别分析（LDA）、支持向量机（SVM）和神经网络（NN）进行了比较，并在7名身体健康的受试者身上进行了测试。在站立阶段，过渡状态和稳定状态的分类错误没有显著性差异（p > 0.05）。在挥杆阶段，肌肉协同方法的表现显著优于NN和LDA（p < 0.01），而结果与SVM相似。这些结果表明，肌肉协同的方法可以用来区分运动模式涉及过渡。
Active lower limb transfemoral prostheses have enabled amputees to perform different locomotion modes such as walking, stair ascent, stair descent, ramp ascent and ramp descent. To achieve seamless mode transitions, these devices either rely on neural information from the amputee's residual limbs or sensors attached to the prosthesis to identify the intended locomotion modes or both. We present an approach for classification of locomotion modes based on the framework of muscle synergies underlying electromyography signals. Neural information at the critical instances (e.g., heel contact and toe-off) was decoded for this purpose. Non-negative matrix factorization was used to extract the muscles synergies from the muscle feature matrix. The estimation of the neural command was done using non-negative least squares. The muscle synergy approach was compared with linear discriminant analysis (LDA), support vector machine (SVM), and neural network (NN) andwas tested on seven able-bodied subjects. There was no significant difference (p > 0.05) in transitional and steady state classification errors during stance phase. The muscle synergy approach performed significantly better (p < 0.01) than NN and LDA during swing phase while results were similar to SVM. These results suggest that the muscle synergy approach can be used to discriminate between locomotion modes involving transitions.