EMG-based Estimation of Muscle Structure and Function

描述（由申请人提供）：本研究的长期目标是了解不同人体肌肉运动单元的结构和行为。运动单元是神经肌肉系统的基本功能单元。肌肉纤维组织成运动单元的方式和运动单元的协调方式是肌肉产生力量和运动能力的重要决定因素。目前唯一可用于研究完整人体单个运动单元的方法包括分析肌电图（EMG）信号。分解多单元肌电信号可以识别单个运动单元放电模式和动作电位波形。动作电位波形的进一步分析提供了关于运动单元结构的信息，包括运动终板和肌肉/肌腱连接的位置。一般来说，肌电图分解，尤其是运动单元体系结构分析，并没有得到尽可能广泛的应用，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关注。我们建议通过开发一种严谨客观的方法来量化分解结果的准确性，为肌电图分解的有效性奠定坚实的科学基础。这将基于位于同一肌肉附近的多个或单个电极的交叉检查结果。我们进一步建议加强和传播我们在过去20年中开发的强大，多功能和准确的肌电图分解程序。所有结果将通过一个网站公布，该网站将作为一个论坛，用于交换与肌电图分解相关的软件、测试信号和信息。拟议的工作将使一个强大的研究工具更值得信赖和更广泛地使用，从而使科学界受益。这一工具将有助于研究人体肌肉的基本结构和功能，并将涉及到几个临床应用，包括肌腱转移和重建手术，中风和脑瘫的康复，以及临床肌电图。

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.