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.

磁脑摄影（MEG）与测量诱导的外部磁场有关映射大脑中的电活动。 该映射适用于诊断癫痫等疾病。 由于弱磁场测量值的稳定改善及其对颅骨内电导率不均匀性的相对鲁棒性的稳定改善，MEG一直是一个非常活跃的区域。 这项研究正在从信号处理的角度开发出多种磁脑电图（MEG）和脑电图（EEG）系统的绩效指标和优化方案。 措施包括：（1）源参数估计值的准确性，（2）基于检测概率的源可检测性，以及（3）源的分辨率或检测多个源的概率。这些措施应用于开发用于MEG/EEG系统参数的最佳设计的技术，包括传感器放置，类型和方向。