Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:3860-3863. doi: 10.1109/EMBC.2017.8037699.
The Modified Ashworth Scale (MAS) is the gold standard in clinical for grading spasticity. However, its results greatly depend on the physician evaluations and are subjective. In this study, we investigated the feasibility of using support vector machine (SVM) to objectively assess elbow spasticity based on both surface electromyography (sEMG) and mechanomyography (MMG). sEMG signals and tri-axial accelerometer mechanomyography (ACC-MMG) signals were recorded simultaneously on patients' biceps and triceps when they extended or bended elbow passively. 39 post-stroke patients participated in the study, and were divided into four groups regarding MAS level (MAS=0, 1, 1+ or 2). The three types of features, root mean square (RMS), mean power frequency (MPF), and median frequency (MF), were calculated from sEMG and MMG signal recordings. Spearman correlation analysis was used to investigate the relationship between the features and spasticity grades. The results showed that the correlation between MAS and each of the five features (MMG-RMS of the biceps, MMG-RMS of the triceps, the EMG-RMS of the biceps, EMG-RMS of the triceps, EMG-MPF of the triceps) was significant (p<;0.05). The four spasticity grades were identified with SVM, and the classification accuracy of SVM with sEMG, MMG, sEMG-MMG were 70.9%, 83.3%, 91.7%, respectively. Our results suggest that using the SVM-based method with sEMG and MMG to assess elbow spasticity would be suitable for clinical management of spasticity.
改良Ashworth量表（MAS）是临床上评估痉挛程度的金标准。然而，其结果很大程度上依赖于医生的评估，具有主观性。在本研究中，我们探讨了使用支持向量机（SVM）基于表面肌电图（sEMG）和机械肌电图（MMG）客观评估肘部痉挛的可行性。当患者被动伸展或弯曲肘部时，同时记录其肱二头肌和肱三头肌的sEMG信号和三轴加速度计机械肌电图（ACC-MMG）信号。39名中风后患者参与了该研究，并根据MAS水平分为四组（MAS = 0、1、1+或2）。从sEMG和MMG信号记录中计算出均方根（RMS）、平均功率频率（MPF）和中位数频率（MF）这三种特征类型。采用Spearman相关性分析来研究这些特征与痉挛等级之间的关系。结果表明，MAS与五个特征（肱二头肌的MMG-RMS、肱三头肌的MMG-RMS、肱二头肌的EMG-RMS、肱三头肌的EMG-RMS、肱三头肌的EMG-MPF）中的每一个之间的相关性均显著（p<0.05）。使用SVM识别出四种痉挛等级，SVM对sEMG、MMG、sEMG-MMG的分类准确率分别为70.9%、83.3%、91.7%。我们的结果表明，使用基于SVM的方法结合sEMG和MMG来评估肘部痉挛适用于痉挛的临床管理。
