System for Non-Invasive EMG Motor Unit Recording

非侵入式肌电图运动单位记录系统

• 批准号: 6937313
• 负责人: Kenneth Shane Guillory
• 金额: $ 9.99万
• 依托单位: RIPPLE, LLC
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6937313
• 关键词: bioimaging /biomedical imaging; biomedical equipment development; carpal tunnel syndrome; clinical research; consumable /disposable biomedical equipment; diagnosis design /evaluation; electromyography; human subject; miniature biomedical equipment; noninvasive diagnosis; patient oriented research; technology /technique development

DESCRIPTION (provided by applicant): The goal of this program is to create a clinical system for non-invasively recording EMG motor unit signals. This system will use Blind Source Deconvolution (BSD) signal processing techniques to collect these signals with surface electrode arrays, rather than needle electrodes that must be inserted and manipulated by highly trained clinicians. This system will improve the speed, cost, and patient comfort of common clinical evaluations that require motor unit recording (such as Carpal Tunnel and diabetic neuropathy), and potentially improve the accuracy and diagnostic sensitivity of surface nerve conduction studies. In addition, by reducing the need for EMG needle insertion and manipulation, this system will enable new remote monitoring and telehealth diagnostic capabilities for common diseases such as Carpal Tunnel Syndrome and diabetic neuropathy. In Phase I, we will verify the ability of Blind Source Deconvolution (BSD) to extract motor unit signals from surface EMG of the thenar muscles using a 256-channel, thin-film EMG electrode array and offline data analysis. In Phase II, we will develop a compact, disposable surface electrode array and a miniaturized data acquisition system with software that implements the BSD algorithms in real-time. This final clinical system will provide audio and video displays of the recordings, quantitative measures regarding the number, size and shape of extracted motor units, and distribution information for the unit conduction velocities.

描述（由申请人提供）：该计划的目标是创建一个用于无创记录肌电图运动单位信号的临床系统。该系统将使用盲源解卷积（BSD）信号处理技术，通过表面电极阵列收集这些信号，而不是必须由训练有素的临床医生插入和操作的针电极。该系统将提高需要运动单位记录（例如腕管和糖尿病神经病变）的常见临床评估的速度、成本和患者舒适度，并有可能提高表面神经传导研究的准确性和诊断灵敏度。此外，通过减少肌电图针插入和操作的需要，该系统将为腕管综合症和糖尿病神经病变等常见疾病提供新的远程监控和远程医疗诊断功能。在第一阶段，我们将验证盲源解卷积（BSD）使用256通道薄膜肌电图电极阵列和离线数据分析从鱼际肌表面肌电图提取运动单元信号的能力。在第二阶段，我们将开发一个紧凑的一次性表面电极阵列和一个小型化数据采集系统，以及实时执行 BSD 算法的软件。最终的临床系统将提供记录的音频和视频显示、有关提取的运动单位的数量、大小和形状的定量测量以及单位传导速度的分布信息。