Motor Unit Numbers Estimation (MUNE) using Bayesian statistical methodology for monitoring of progression of neuromuscular diseases

使用贝叶斯统计方法监测神经肌肉疾病进展的运动单位数估计 (MUNE)

• 批准号: LP0455317
• 负责人: Prof Anthony Pettitt
• 金额: $ 10.55万
• 依托单位: Queensland University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2004
• 资助国家: 澳大利亚
• 起止时间: 2004-11-17 至 2008-06-30
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0455317
• 关键词: Motor; Unit; Numbers; Estimation; MUNE

A means of objectively measuring the pathology of a neuromuscular disease involving motor unit loss, such as motor neuron disease, is much needed. This will be achieved by using newly developed electrophysiological techniques and developing new Bayesian statistical methodology to determine the number of motor units that supply a muscle. Our innovations will reliably determine the number of motor units that supply a muscle in both normal subjects and in diseased patients with loss of motor nerves. This will enable the monitoring of disease progression. An outcome will be a software package that can be used with standard electrophysiology machines.

客观地测量涉及运动单位丢失的神经肌肉疾病的病理学，例如运动神经元病，是非常必要的。这将通过使用新开发的电生理技术和开发新的贝叶斯统计方法来确定供应肌肉的运动单位的数量来实现。我们的创新将可靠地确定在正常人和运动神经丧失的疾病患者中供应肌肉的运动单位的数量。这将使监测疾病进展成为可能。结果将是一个可以与标准电生理学机器一起使用的软件包。