Quantitative Electrophysiological Neuromuscular Characterization

通过分析神经和肌肉产生的电生理信号来研究它们的结构和活动。肌电图（EMG）信号用于研究影响骨骼肌形态和生理的过程。骨骼肌被组织成运动单位（mu）；由单个运动神经元激活的纤维群。每个MU产生运动单位电位（MUPs），这是由活跃的MU纤维产生的肌纤维电位（mfp）的总和。在肌肉收缩过程中，小肌重复活动。每个活动MU产生一个运动单元电位序列（motor unit potential train， MUPT），肌电信号是活动MU的MUPT之和。神经肌肉疾病和衰老影响MUs的形态和生理，以及它们产生的mfp、MUPs和mupt。目前，许多神经肌肉疾病的诊断依赖于对针刺肌电信号的MUPs和mupt的主观和定性分析。因此，患者的预后高度依赖于个别医生的专业知识和培训，很难评估疾病进展并提供可靠的预后。目前对衰老的神经肌肉效应的研究使用复合肌电信号的统计，不能提供详细的个体MU信息。因此，这些方法无法检测重要的神经肌肉变化。

The structures and actions of nerves and muscles are studied by analyzing the electrophysiological signals they generate. Electromyographic (EMG) signals are used to study processes affecting skeletal muscle morphology and physiology. Skeletal muscles are organized into motor units (MUs); groups of fibres activated by single motor neurons. Each MU generates motor unit potentials (MUPs), which are summations of muscle fibre potentials (MFPs) generated by active MU fibres. During muscle contraction, MUs are repetitively active. Each active MU generates a motor unit potential train (MUPT), and an EMG signal is the summation of the MUPTs of active MUs. Neuromuscular disorders and aging affect the morphology and physiology of MUs, and the MFPs, MUPs and MUPTs they generate. Currently, the diagnosis of many neuromuscular disorders relies on subjective and qualitative analysis of the MUPs and MUPTs of needle-detected EMG signals. Patient outcomes are therefore highly dependent on individual physician expertise and training, and it is very difficult to assess disease progression and provide reliable prognoses. Current studies of the neuromuscular effects of aging use statistics of composite EMG signals, which cannot provide detailed individual MU information. As such, these methods are unable to detect important neuromuscular changes.