Relating biceps EMG to elbow kinematics during self-paced arm flexions

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• 作者：Gautam S. Natarajan^a ; ^{GSN993@gmail.com} ; Michael Wininger^b ; ^c ; Nam H. Kim^d ; William Craelius^a
• 关键词：Arm ; Reaching ; Variability ; Elbow ; EMG ; Kinematics ; Flexion ; Trajectory prediction ; Support vector machines ; Prosthetic control
• 刊名：Medical Engineering and Physics
• 出版年：2012
• 期刊代码：196_13504533
• 类别：med
• 出版时间：June, 2012
• 卷：34
• 期：5
• 页码：617-624
• 文件大小：923 K

摘要

Repetitive reaching movements to a fixed target can be generally characterized by bell-shaped velocity profiles and sigmoidal trajectories with variable morphologies across multiple repetitions. A neuromuscular correspondence of these kinematic variations has thus far eluded electromyographic (EMG) analysis. We recorded EMG and elbow kinematics from fourteen healthy individuals performing repetitive, self-paced, isolated elbow flexions, with their arms supported against gravity. The global kinematic pattern of each flexion was classified as either sigmoidal (S) or non-sigmoidal (NS), based on goodness of fit with analytical curves. Ten of the fourteen subjects generated an approximately equal number of S and NS types (383 movement cycles). Trajectories of the other four subjects were not classifiable or did not vary sufficiently and were excluded from subsequent analysis. A post hoc predictor of trajectory type was derived by testing linear support vector machines trained with a strategically selected 3-feature sub-space of the early phase of enveloped biceps EMG during a leave-one-out cross-validation paradigm. Results showed that EMG features predicted kinematic morphology with sensitivity and specificity both exceeding 80%. The high predictive accuracy suggests neuromotor signals coding for subtle variations in elbow kinematics during self-paced, unloaded motions, can be deciphered from the biceps EMG.