EMG-based Estimation of Muscle Structure and Function

描述(申请人提供)：这项研究的长期目标是了解不同人体肌肉中运动单位的结构和行为。运动单位是神经肌肉系统的基本功能单位。肌肉纤维组织成运动单位的方式和运动单位协调的方式是肌肉产生力量和运动的能力的重要决定因素。目前可用于研究完整人类单个运动单位的唯一方法是分析肌电(EMG)信号。多单位肌电信号的分解可以识别单个运动单位的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位结构的信息，包括运动终板和肌肉/肌腱连接的位置。一般说来，肌电分解，特别是运动单元结构分析，并没有得到尽可能广泛的利用，这在很大程度上是因为缺乏可用的软件，以及对分解有效性的担忧。我们建议通过发展一种严谨和客观的方法来量化分解结果的准确性，从而为肌电分解的有效性奠定坚实的科学基础。这将基于对位于同一肌肉中邻近部位的多个或单个单位电极所获得的交叉核对结果。我们还建议加强和传播我们在过去20年中开发的强大、通用和准确的EMG分解程序。所有结果将通过一个互联网站提供，该网站将作为交流软件、测试信号和与肌电分解相关的信息的论坛。拟议的工作将使一种强大的研究工具更值得信赖和更广泛地获得，从而使科学界受益。这一工具将有助于研究人类肌肉的基本结构和功能，并将在肌腱转移和重建手术、中风和脑瘫的康复以及临床肌电图等临床应用中发挥重要作用。

DESCRIPTION (provided by applicant): 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.