Digital Signal Processing in Real-time for Magneto-electrical Sensor Systems

磁电传感器系统的实时数字信号处理

• 批准号: 269991101
• 负责人: Professor Dr. Günther Deuschl
• 金额: --
• 依托单位: Arbeitsgruppe Digitale Signalverarbeitung und Systemtheorie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/269991101?language=en
• 关键词: Digital; Signal; Processing; Real; time

This research proposal focuses on real-time processing for new magneto-electrical sensor systems, which are able to operate at room temperature. With those sensors (and the corresponding signal processing techniques) medically relevant research questions in the area of neurology should be addressed. The objectives are to enhance already existing signal detection, estimation, and enhancement algorithms but also to design new adaptive processing schemes. The focus of these algorithms should be on real-time implementations. The entire proposal is structured in three parts:1. A multi-channel real-time system should be built up, which is capable of connecting a multitude of magneto-electrical, electrical, and acoustic as well as acceleration sensors. All of these inputs should be equalized in an optimal manner. Background, amplifier, and other noise types should be suppressed. Exogenous noise sources should be cancelled using a combined approach consisting of a beamforming and a cancellation stage.2. The enhanced signals obtained from part 1 will be processed by a second stage in order to remove endogenous artifacts as they appear due to heart beats, eye blinks, or muscle activity. This processing stage is designed based on state-space approaches.3. Based on the DICS algorithm (DICS is a shortcut for Dynamic Imaging of Coherent Sources) an innovative source localization in real time will be investigated. For this purpose the further enhanced signals of part 2 will be used.The results of all three parts of this proposal interact. If, e.g., the coherence analysis and source localization detect the origin of a neurologic network in a certain area, the magneto-electrical sensors can be adjusted and leveled towards this origin after a short measurement. As a result the spatial resolution of the analysis will improve. This also applies to the optimal use of the bandwidth of the magneto-electrical sensors. Currently the bandwidth of the sensors is between 10 and 30 Hz and therefore not comparable to conventional (SQUID based) sensors. With the help of a frequency shift the maximum sensor sensitivity can be aligned adaptively. If a frequency range of interest is determined based on a preliminary analysis, the demodulation of the sensors can be adapted. Consequently the frequency range of interest will be investigated with the optimal signal-to-noise ratio. This leads to the development of a closed control loop, which justifies the real-time requirement of this research proposal.

该研究计划的重点是新的磁电传感器系统，这是能够在室温下工作的实时处理。有了这些传感器（和相应的信号处理技术），神经病学领域的医学相关研究问题应该得到解决。我们的目标是提高现有的信号检测，估计和增强算法，但也设计新的自适应处理方案。这些算法的重点应该放在实时实现上。整个提案分为三个部分：1. 应建立一个多通道实时系统，该系统能够连接多个磁电、电、声以及加速度传感器。所有这些输入都应该以最佳方式均衡。背景、放大器和其他噪声类型应得到抑制。外生噪声源应使用由波束形成和消除阶段组成的组合方法来消除。 从第1部分获得的增强信号将通过第二阶段进行处理，以去除由于心跳、眨眼或肌肉活动而出现的内源性伪影。该处理阶段是基于状态空间方法设计的. 基于DICS算法（DICS是相干源动态成像的一种捷径），本文将研究一种新的真实的实时源定位方法。为此目的，将使用第2部分的进一步增强的信号。本建议的所有三个部分的结果相互作用。如果，例如，相干性分析和源定位检测某个区域中的神经网络的起源，在短暂的测量之后，可以将磁电传感器调整并调平到该起源。因此，分析的空间分辨率将提高。这也适用于磁电传感器带宽的最佳使用。目前，传感器的带宽在10和30 Hz之间，因此无法与传统的（基于SQUID的）传感器相比。在频移的帮助下，最大传感器灵敏度可以自适应地对准。如果基于初步分析确定了感兴趣的频率范围，则可以调整传感器的解调。因此，感兴趣的频率范围将与最佳的信噪比进行研究。这导致了一个闭环控制回路的发展，这证明了本研究建议的实时要求。