Decision Support for Clinical Neurophysiology

临床神经生理学的决策支持

• 批准号: 44330-2012
• 负责人: Stashuk, Daniel
• 金额: $ 1.24万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=521704
• 关键词: Decision; Support; Clinical; Neurophysiology

Disorders of muscle and nerve change the structure and organization of the muscles involved. Characteristics of clinical electromyographic (EMG) signals suitably detected from affected muscles reflect the degree and type of disorder present. Physicians currently, subjectively and qualitatively, assess EMG signal characteristics to support diagnosis, treatment and management of specific disorders. This assessment is highly dependent on physician skill and experience. Furthermore, assessment of the severity of involvement and the sensitivity with which progressive changes can be tracked is limited. Quantitative electromyography (QEMG) involves the detection and analysis of EMG signals to calculate statistics for neuromuscular characterization. QEMG can improve the specificity and sensitivity of neuromuscular assessments and track longitudinal changes associated with specific treatment or management regimes. However, a method for completing the crucial step of interpreting QEMG data to produce a neuromuscular characterization is currently needed.

肌肉和神经的紊乱改变了相关肌肉的结构和组织。从受累肌肉适当检测到的临床肌电(EMG)信号的特征反映了目前存在的障碍的程度和类型。目前，医生在主观上和定性上评估肌电信号特征，以支持特定疾病的诊断、治疗和管理。这项评估高度依赖于医生的技能和经验。此外，对参与的严重性和跟踪渐进变化的敏感度的评估是有限的。定量肌电图(QEMG)包括对肌电信号的检测和分析，以计算神经肌肉特征的统计数据。QEMG可以提高神经肌肉评估的特异性和敏感性，并跟踪与特定治疗或管理制度相关的纵向变化。然而，目前需要一种方法来完成解释QEMG数据以产生神经肌肉特征这一关键步骤。