Clinical characterization of muscle using quantitative electromyographic signal analysis

神经肌肉疾病改变了所涉及的肌肉及其运动单位(MU)的结构和组织。从受影响的肌肉中适当检测到的肌电(EMG)信号的特征可以反映存在的疾病的类型和严重程度。对信号特征的正确解释有助于诊断、治疗和管理。目前，肌电信号被主观和定性地评估与神经或肌肉疾病、慢性化和严重性相一致的特征。这种评估是主观的，在一定程度上，高度依赖于检查医生的技能和经验，而且可以跟踪渐进性变化的程度是有限的。定量肌电(QEMG)分析可以提供更客观、一致和灵敏的电生理特征。然而，能够临床获取QEMG数据的应用很少，更重要的是，目前还没有完成解释QEMG数据以产生神经肌肉系统特征的关键步骤的方法。因此，这项研究的目标是为肌电临床常规使用的肌电信号采集、QEMG分析和电生理特征提供一个集成的系统。此外，将为每个特征提供全面和直观的理由以及有效的置信度测量，以支持改进的临床决策。新系统的新方面将包括：采集、分析和解释的一体化；信号采集的简单性和一致性，所提供的QEMG数据的有效性；以及电生理特征的价值。除了促进QEMG数据的获取和质量之外，这项工作的主要意义将是改进QEMG数据的解释，这将有助于更好地诊断、治疗和管理神经肌肉疾病。此外，在肌电诊所证明能够轻松完成这些研究，将增加这些方法被转化到其他临床肌电机器以产生广泛影响的可能性。

Neuromuscular disorders change the structure and organization of the muscles involved and their complement of motor units (MUs). Characteristics of electromyographic (EMG) signals suitably detected from affected muscles can reflect the type and severity of disorder present. Proper interpretation of signal characteristics can assist with diagnosis, treatment and management. Currently, EMG signals are subjectively and qualitatively assessed for features consistent with nerve or muscle disease, chronicity, and severity. This assessment is subjective, and in part, highly dependent on the skill and experience of the examining physician and the extent to which progressive changes can be tracked is limited. Quantitative EMG (QEMG) analysis allows for a more objective, consistent and sensitive electrophysiological characterization. However, few applications capable of clinically acquiring QEMG data exist and more importantly a method for completing the crucial step of interpreting QEMG data to produce a characterization of the neuromuscular system is currently not available. The objectives of the proposed research are therefore to produce an integrated system for EMG signal acquisition, QEMG analysis and electrophysiological characterization for routine use in an EMG clinic. In addition, a comprehensive and intuitive rationale, and a valid measure of confidence will be provided for each characterization to support improved clinical decisions. Novel aspects of the new system will include: the integration of acquisition, analysis and interpretation; the ease and consistency of signal acquisition, the validity of the QEMG data provided; and the value of the electrophysiological characterization. Beyond facilitating the acquisition and quality of QEMG data, the main significance of this work will be improved interpretation of QEMG data which will contribute to better diagnosis, treatment and management of neuromuscular disorders. Furthermore, demonstrating an ability to readily complete these studies in an EMG clinic will increase the likelihood of the methods being translated to other clinical EMG machines for widespread impact.