EMG-based Estimation of Muscle Structure and Function

这项研究的长期目标是了解不同类型的运动单元的结构和行为。 人类的肌肉。运动单位是神经肌肉系统的基本功能单位。以一种方式 肌肉纤维被组织成运动单位，运动单位的协调方式很重要 肌肉产生力量和运动能力的决定因素。目前唯一可用的方法是 研究完整人体的单个运动单位需要分析肌电(EMG)信号。 多单位肌电信号的分解允许识别单独的运动单位放电模式和 动作电位波形。对动作电位波形的进一步分析提供了有关 运动单元结构，包括运动终板和肌肉/肌腱连接的位置。肌电 一般说来，分解，特别是电机单元架构分析，并不像它们那样被广泛使用 可能是，很大程度上是因为缺乏可用的软件，以及对有效性的担忧 腐烂。我们建议为肌电分解的有效性奠定坚实的科学基础 通过开发一种严格和客观的方法来量化分解结果的准确性。这 将基于从附近地点的多个或单个单元电极获得的交叉核对结果 在同一块肌肉里。我们还建议加强和传播一个强大、通用和准确的 我们在过去20年里开发的肌电分解程序。所有的结果都将被公布 可通过互联网站获得，该网站将作为交换软件、测试信号和 与肌电分解相关的信息。拟议的工作将使科学界受益于 使强大的研究工具更值得信赖，更广泛地可用。此工具将对以下方面有用 研究人体肌肉的基本结构和功能，将对临床上几个方面有一定的指导意义 应用，包括肌腱转移和重建手术，中风和脑瘫的康复， 和临床肌电图。

The long-term goal of this research is to understand the architecture and behavior of motor units in different human muscles. The motor unit is the basic functional unit of the neuromuscular system. The way in which muscle fibers are organized into motor units and the way in which motor units are coordinated are important determinants of a muscle's ability to produce force and movement. The only method currently available for studying individual motor units in intact humans involves analyzing electromyographic (EMG) signals. Decomposition of multi-unit EMG signals allows identification of individual motor-unit discharge patterns and action-potential waveforms. Further analysis of the action-potential waveforms provides information about motor-unit architecture, including the locations of motor endplates and muscle/tendon junctions. EMG decomposition in general, and motor-unit architecture analysis in particular, are not utilized as widely as they could be, in large part because of the lack of available software and because of concerns about the validity of decomposition. We propose to establish a firm scientific foundation for the validity of EMG decomposition by developing a rigorous and objective method for quantifying the accuracy of decomposition results. This will be based on cross-checking results obtained from multi- or single-unit electrodes located at nearby sites in the same muscle. We further propose to enhance and disseminate a powerful, versatile, and accurate EMG decomposition program that we have developed over the past 20 years. All results will be made available via an internet site that will serve as a forum for the exchange of software, test signals, and information related to EMG decomposition. The proposed work will benefit the scientific community by making a powerful research tool more trustworthy and more widely available. This tool will be useful for studying the basic structure and function of human muscles, and it will be relevant to several clinical applications, including tendon-transfer and reconstructive surgery, rehabilitation in stroke and cerebral palsy, and clinical electromyography.