Magnetoencephalography Performance Measures and Optimizations

脑磁图性能测量和优化

• 批准号: 9615590
• 负责人: Arye Nehorai
• 金额: $ 24.41万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-03-01 至 2000-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9615590&HistoricalAwards=false
• 关键词: Magnetoencephalography; Performance; Measures; Optimizations

MagnetoEncephaloGraphy (MEG) is concerned with mapping electrical activity in the brain by measuring the induced external magnetic field. This mapping is applied for diagnosis of diseases such as epilepsy. MEG has been a very active area lately due to the steady improvement of weak magnetic field measurements and its relative robustness to inhomogeneities in electrical conductivity within the skull. This research is developing several performance measures and optimization schemes for magnetoencephalography (MEG) and electroencephalography (EEG) systems, from a signal processing point of view. The measures include: (1) accuracy of source parameter estimates, (2) detectability of a source, based on the probability of detection, and (3) resolution of sources, or the probability of detecting more than one source. These measures are being applied to develop techniques for the optimum design of MEG/EEG system parameters, including sensor placement, type and orientation.

脑磁图（MEG）涉及通过测量感应的外部磁场来绘制大脑中的电活动。 该映射应用于诸如癫痫的疾病的诊断。 最近，由于弱磁场测量的稳步改进及其对颅骨内电导率不均匀性的相对鲁棒性，MEG一直是一个非常活跃的领域。 本研究从信号处理的角度出发，针对脑磁图（MEG）和脑电图（EEG）系统开发了几种性能指标和优化方案。 这些措施包括：（1）源参数估计的准确性，（2）基于检测概率的源的可检测性，以及（3）源的分辨率，或检测多于一个源的概率。这些措施正被用于开发脑磁/脑电系统参数的最佳设计技术，包括传感器的放置、类型和方向。