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Mixed-signal micropower VLSI systems for biomedical array signal processing.

机译:用于生物医学阵列信号处理的混合信号微功率VLSI系统。

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摘要

Sensor array signal processing is ubiquitous in a variety of biomedical applications. Constraints on power and size of implantable and wearable systems dictate custom design of highly integrated solutions. This dissertation presents a design methodology for low-power integrated biomedical microsystems interfacing with sensor arrays, with application to intelligent hearing aids and implantable neural interfaces.; First I present mixed-signal VLSI adaptive microsystems interfacing with miniature microphone arrays that perform acoustic source separation and localization at microwatts of power, for use in intelligent hearing aids and acoustic surveillance. Analog gradient sensing of the broadband travelling wave field at sub-wavelength scale across a planar array of sensors yields linearly mixed instantaneous observations of multiple sources, blindly separated and 3-D localized using independent component analysis. A mixed-signal VLSI implementation of gradient flow for 3-D bearing estimation has experimentally demonstrated one degree angular resolution in localizing a broadband acoustic source at 20dB signal-to-noise ratio. The chip was integrated in an Acoustic Surveillance Unit (ASU) for autonomous acoustic sensing of the battlefield with superior accuracy in localizing ground vehicles compared to commercial systems of considerably larger size and power budget. The real-time system, comprising of the gradient flow VLSI processor and reconfigurable mixed-signal VLSI implementation of independent component analysis (ICA), experimentally demonstrates perceptually clear (12dB) separation and precise localization of two speech sources presented through speakers positioned at 1.5 m from the array on a conference room table.; Second I present microsystems for implantable neural recording. Implanted neural interfaces facilitate understanding of neurological phenomena and allow for automated medical diagnostics. A 16-channel current measuring VLSI potentiostat is presented for electrochemical detection of electroactive neurotransmitters like dopamine, nitric oxide etc. The current measurement capability spans six orders of magnitude in dynamic range down to hundreds of femtoamperes through innovative micropower design in analog-to-digital conversion. Real-time multi-channel acquisition of dopamine concentration in vitro with a microfabricated sensor array demonstrates ability of the system to be integrated in implantable monitoring system.
机译:传感器阵列信号处理在各种生物医学应用中无处不在。植入式和可穿戴系统的功率和尺寸的限制决定了高度集成解决方案的定制设计。本文提出了一种与传感器阵列接口的低功耗集成生物医学微系统的设计方法,并应用于智能助听器和可植入神经接口。首先,我介绍了与微型麦克风阵列接口的混合信号VLSI自适应微系统,该系统以微瓦的功率执行声源分离和定位,用于智能助听器和声学监视。跨越传感器平面阵列的亚波长尺度上的宽带行波场的模拟梯度感测,可以通过独立分量分析对多个源进行盲目分离和3-D本地化的线性混合瞬时观测。用于3-D方位估计的梯度流的混合信号VLSI实现在实验上证明了将宽带声源定位在20dB信噪比时的一度角分辨率。该芯片被集成到声学监视单元(ASU)中,用于战场的自主声学感应,与尺寸和功率预算大得多的商用系统相比,在定位地面车辆方面具有更高的精度。该实时系统由梯度流VLSI处理器和独立成分分析(ICA)的可重配置混合信号VLSI实现组成,通过实验证明了通过位于1.5 m处的扬声器呈现的两个语音源在感知上清晰(12dB)分离和精确定位来自会议室桌子上的阵列。其次,我介绍了用于植入式神经记录的微系统。植入的神经接口有助于理解神经系统现象,并允许进行自动医学诊断。提出了一种用于电化学检测多巴胺,一氧化氮等电活性神经递质的16通道电流测量VLSI稳压器。通过创新的微功耗设计(模数转换),电流测量能力在动态范围内跨越了六个数量级,低至数百飞安。转换。利用微制造的传感器阵列在体外实时多通道采集多巴胺浓度,证明了该系统能够集成到可植入监测系统中的能力。

著录项

  • 作者

    Stanacevic, Milutin.;

  • 作者单位

    The Johns Hopkins University.;

  • 授予单位 The Johns Hopkins University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 120 p.
  • 总页数 120
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

  • 入库时间 2022-08-17 11:39:38

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