Research about Motor Unit Visualization with Surface EMG Signals

本研究主要针对运动单位的分解以及从表面肌电信号中显示活动的方法进行了如下研究：（1）运动单位分解技术的改进我们提出了一种新的基于过完备基的运动单位分解技术来引入统计模型。实验结果表明，该方法应用于真实的测量表面肌电信号，具有与盲解卷积相当的分解性能。此外，还证实了即使观察通道的数量小于活动运动单元的数量，每个运动单元的活动也可以是可分离的。B）使用统计模型的识别技术的有效性检验我们提出了使用KDA和Boosting机制的识别系统，并证实了它的识别性能就像现有的技术如SVM一样。一般来说，为了最大化泛化性能，参数调整过程，如交叉验证，其计算 关于我们 在成本上是非常昂贵的，是需要的。为了解决这个问题，我们提出了一个新的参数选择指标值，在不增加计算成本的情况下，可以选择合适的参数。每个运动单位的三维位置估计由运动单位估计的皮肤表面电位分布，用三维有限元方法估计每个运动单位去极化的三维位置分解技术从表面肌电信号。其结果是，它被证实，3D位置和动态的dopolarization个别运动单位可以估计。此外，神经支配区的大小和去极化电流强度的时间动态可以估计。此外，这项研究已开始在2003财政年度的首席研究员，小谷博士助理教授科比大学。然而，他在2004年5月去世，所以头部突然改变。我写下小谷博士的贡献涵盖了上述结果的全部。少

This research was executed for the motor unit decomposition and making the activity visible from the surface electromyogram as follows.A)Improvement of motor unit decomposition techniqueWe proposed a new motor unit decomposition technique with overcomplete bases to introduce the statistical model. It was confirmed that this technique was applied to the real measurement surface EMG signals, and it had the decomposition performance equal with blind deconvolution. Moreover, it was confirmed that each motor unit activity might be separable even if the number of observation channels were less than the number of active motor units.B)Examination of effectiveness of recognition technique using statistical modelWe proposed the recognition system using both KDA and boosting mechanism and confirmed that it's recognition performance was just like an existing technique such as SVM. In general, to maximize generalization performance, parameter tuning process such as cross validation, whose computati … More on cost is very expensive, is needed. To solve this problem, we proposed new index value for parameter selection, and with this index, appropriate parameters can be selected without so expensive computation cost.C)The three dimensional position estimation of each decomposed motor unitThe 3D position of the depolarization of individual motor unit was estimated by using the 3D finite element method from the potential distribution on the skin surface which was estimated with motor unit decomposition technique from surface EMG signals. As a result, it was confirmed that 3D position and dynamics of dopolarization of individual motor unit might be estimated. Moreover, the size of innervation zone and temporal dynamics of current intensity of depolarization could be estimated.In addition, this study had been started in 2003 fiscal year under Dr.Kotani head researcher, Assistant Professor of Kobe University. However he died in May, 2004, so the head was changed suddenly. I write down that contribution of Dr.Kotani covers the whole of the above results. Less