SBIR Phase I: Information Theoretic Learning and Application to Fetal ECG

这个小企业创新研究（SBIR）第一阶段项目的重点是基于最近提出的信息理论学习（ITL）标准开发和评估一类新的盲源分离（BSS）和独立分量分析（ICA）算法。算法产生了几个实用的标准来适应通用映射器，无论是在无监督范式还是有监督范式下。ITL准则可以显著改善用均方误差训练的系统。NeuroDimension将开发新的算法来选择用于分离的片段，解决噪声混合的BSS问题，并将ITL准则扩展到卷积混合。该公司进一步提出通过胎儿心率监测问题来验证这些方法，这需要分离母体和胎儿的心电图，这是一个盲源分离问题。最小交叉熵的ITL准则可以利用心电图在统计上独立的事实。期望新的信息理论学习将提取一个更清晰的心电，因为它利用了信号统计的所有信息，而不仅仅是二阶统计信息（如MSE所做的）。最后，将ITL准则与佛罗里达大学医学院实际数据中的传统干扰消除算法进行比较。这个项目有潜力开发出一种新的临床仪器，一种胎儿心脏监测器，它有一个示范市场。该公司利用一种新的信息信号处理方法，可能能够以一种实用的、实时的方式识别难以捉摸的胎儿心脏信号。

This Small Business Innovation Research (SBIR)Phase I project focuses on the development and evaluation of a new class of algorithms for blind source separation (BSS) and independent component analysis (ICA) based on a recently proposed information theoretic learning (ITL) criterion. The algorithms yield several practical criteria to adapt universal mappers, either under unsupervised or supervised paradigms. The ITL criterion can dramatically improve upon systems trained with mean square error. NeuroDimension will develop new algorithms to choose the segments for separation, address BSS of noisy mixtures, and extend the ITL criterion to convolutive mixtures. The firm further proposes to validate these methods via the fetal heart rate monitoring problem, which requires the separation of the maternal and fetal ECGs, a blind source separation problem. The ITL criterion of minimum cross entropy can exploit the fact that the ECGs are statistically independent. The expectation is that the new information theoretic learning will extract a much cleaner ECG because it is exploiting all the information about the signal statistics, not only the second order statistics (as MSE does). Finally the ITL criterion will be compared with the conventional interference cancellation algorithms in real data obtained from the University of Florida College of Medicine. The project has the potential to develop a new piece of clinical instrumentation, a fetal heart monitor, for which there is a demonstrated market. The firm utilizes a new approach to information signal process that may be able to identify the elusive fetal heart signal in a practical, real-time manner.