Liu Yang, Ning Yong, Li Sheng, Zhou Ping, Rymer William Z, Zhang Yingchun
Department of Biomedical Engineering, University of Houston, 3605 Cullen Blvd, Houston, TX77004, USA.
Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, 7000 Fannin St., Houston, TX, USA.
Int J Neural Syst. 2015 Sep;25(6):1550024. doi: 10.1142/S0129065715500240.
There is an unmet need to accurately identify the locations of innervation zones (IZs) of spastic muscles, so as to guide botulinum toxin (BTX) injections for the best clinical outcome. A novel 3D IZ imaging (3DIZI) approach was developed by combining the bioelectrical source imaging and surface electromyogram (EMG) decomposition methods to image the 3D distribution of IZs in the target muscles. Surface IZ locations of motor units (MUs), identified from the bipolar map of their MU action potentials (MUAPs) were employed as a prior knowledge in the 3DIZI approach to improve its imaging accuracy. The performance of the 3DIZI approach was first optimized and evaluated via a series of designed computer simulations, and then validated with the intramuscular EMG data, together with simultaneously recorded 128-channel surface EMG data from the biceps of two subjects. Both simulation and experimental validation results demonstrate the high performance of the 3DIZI approach in accurately reconstructing the distributions of IZs and the dynamic propagation of internal muscle activities in the biceps from high-density surface EMG recordings.
准确识别痉挛肌肉的神经支配区(IZs)位置以指导肉毒杆菌毒素(BTX)注射从而获得最佳临床效果的需求尚未得到满足。通过结合生物电源成像和表面肌电图(EMG)分解方法,开发了一种新颖的3D神经支配区成像(3DIZI)方法,以对目标肌肉中IZs的三维分布进行成像。从运动单位(MUs)的双极图中识别出的MUs的表面IZ位置,在3DIZI方法中用作先验知识,以提高其成像精度。首先通过一系列设计的计算机模拟对3DIZI方法的性能进行优化和评估,然后用肌内EMG数据以及同时记录的来自两名受试者肱二头肌的128通道表面EMG数据进行验证。模拟和实验验证结果均表明,3DIZI方法在从高密度表面EMG记录中准确重建IZs分布以及肱二头肌内部肌肉活动的动态传播方面具有高性能。