Cheng Hang-Shing, Ju Ming-Shaung, Lin Chou-Ching K
Department of Mechanical Engineering, National Cheng Kung University, Tainan, Taiwan.
Muscle Nerve. 2005 Nov;32(5):589-99. doi: 10.1002/mus.20404.
The afferent signals recorded with a multi-electrode cuff on the sciatic nerve were employed to investigate the possibility of extracting components ascending from the peroneal and tibial nerves. Two methods, an inverse regression model and principal component method, were studied. The parameters of inverse regression model, determined by data collected in semistatic conditions, were validated by data collected in dynamic conditions. The results showed that the regression model, which used only two channels of the sciatic recordings, was sufficient to separate the distal afferent components. The model, at the expense of requiring distal branch recordings for estimating model parameters, yielded better separation than the principal component method. In conclusion, peroneal and tibial afferent activity can be estimated from the sciatic nerve: the principal component method is suitable for applications focused on acquiring afferent information, whereas the inverse regression model is better for applications in which stimulations will be applied to the branches. The estimation technique provides a powerful tool for in vivo investigation of sensory information transmitted in a peripheral nerve and facilitates implementation of advanced functional neuromuscular stimulation systems.
用多电极袖套记录坐骨神经上的传入信号，以研究从腓神经和胫神经提取上行成分的可能性。研究了两种方法，即逆回归模型和主成分法。通过半静态条件下收集的数据确定逆回归模型的参数，并通过动态条件下收集的数据进行验证。结果表明，仅使用坐骨神经记录的两个通道的回归模型足以分离远端传入成分。该模型虽然需要远端分支记录来估计模型参数，但比主成分法产生了更好的分离效果。总之，腓神经和胫神经的传入活动可以从坐骨神经中估计出来：主成分法适用于专注于获取传入信息的应用，而逆回归模型更适合于将刺激应用于分支的应用。该估计技术为体内研究外周神经中传递的感觉信息提供了一个强大的工具，并有助于先进功能性神经肌肉刺激系统的实施。
