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能力的重要决定因素。目前唯一可用于研究完整人类个体运动单位的方法涉及分析肌电图（EMG）信号。多单元EMG信号的分解允许识别单个电机单元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。一般的EMG分解，特别是运动单元结构分析，并没有被广泛使用，因为它们可以，在很大程度上是因为缺乏可用的软件，因为分解的有效性的关注。我们建议建立一个坚实的科学基础的有效性肌电信号分解，通过开发一个严格的和客观的方法量化的分解结果的准确性。这将基于从位于同一肌肉附近部位的多单元或单单元电极获得的交叉检查结果。我们进一步建议加强和传播一个强大的，多功能的，准确的EMG分解程序，我们已经开发了过去20年。所有结果将通过互联网网站提供，该网站将作为交换软件、测试信号和EMG分解相关信息的论坛。拟议的工作将使科学界受益，使一个强大的研究工具更值得信赖，更广泛地提供。该工具将有助于研究人体肌肉的基本结构和功能，并将与几种临床应用相关，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.