摘要翻译：
本文的目的是介绍目前的技术进展，这些技术可以开发出完全可饮用和自主的生物电子CMOS传感器，以灰尘颗粒的形式，能够通过瞄准器官和组织的特定区域如肿瘤肿块来识别疾病的来源，并自动在体外无线发送诊断信息。我们称这群感应尘粒为体尘。人体灰尘形式的诊断系统需要足够小，以支持人体组织的自由循环，这要求总尺寸小于10微米，以模拟血细胞的典型尺寸（例如，红细胞的直径约为7{\\μ}米）。虽然在CMOS技术的目前最先进的状态下，在尺寸方面的这一要求目前是不可行的，但最近的研究有了先进的技术，使我们可以开始朝着这样的方法努力。因此，我们在这里提出了CMOS技术的当前限制以及与开发这样一个系统相关的挑战。为了实现这一目标，本文提出了获得第一个具有生物传感能力的亚10um Bio/CMOS集成电路的理论可行性，该集成电路一旦在人体组织中自我定位，就可以提供诊断遥测。
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英文标题：
《Body Dust: Miniaturized Highly-integrated Low Power Sensing for Remotely
  Powered Drinkable CMOS Bioelectronics》
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作者：
Sandro Carrara and Pantelis Georgiou
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最新提交年份：
2018
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分类信息：

一级分类：Physics        物理学
二级分类：Applied Physics        应用物理学
分类描述：Applications of physics to new technology, including electronic devices, optics, photonics, microwaves, spintronics, advanced materials, metamaterials, nanotechnology, and energy sciences.
物理学在新技术中的应用，包括电子器件、光学、光子学、微波、自旋电子学、先进材料、超材料、纳米技术和能源科学。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Physics        物理学
二级分类：Biological Physics        生物物理学
分类描述：Molecular biophysics, cellular biophysics, neurological biophysics, membrane biophysics, single-molecule biophysics, ecological biophysics, quantum phenomena in biological systems (quantum biophysics), theoretical biophysics, molecular dynamics/modeling and simulation, game theory, biomechanics, bioinformatics, microorganisms, virology, evolution, biophysical methods.
分子生物物理、细胞生物物理、神经生物物理、膜生物物理、单分子生物物理、生态生物物理、生物系统中的量子现象（量子生物物理）、理论生物物理、分子动力学/建模与模拟、博弈论、生物力学、生物信息学、微生物、病毒学、进化论、生物物理方法。
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一级分类：Physics        物理学
二级分类：Medical Physics        医学物理学
分类描述：Radiation therapy. Radiation dosimetry. Biomedical imaging modelling.  Reconstruction, processing, and analysis. Biomedical system modelling and analysis. Health physics. New imaging or therapy modalities.
放射治疗。辐射剂量学。生物医学成像建模。重建、处理和分析。生物医学系统建模与分析。健康物理学。新的成像或治疗方式。
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英文摘要：
  The aim of this paper is to introduce current advances in technology that could enable the development of fully drinkable and autonomous bio-electronic CMOS sensors in the form of dust particles, capable of identifying the source of a disease by targeting a specific region in organs and tissue such as a tumor mass and automatically sending diagnostic information wirelessly outside the body. We call this swarm of sensing dust particles Body Dust. A diagnostic system in the form of Body Dust would need to be small enough to support free circulation in human tissues, which requires a total size of less than 10 um3, in order to mimic the typical sizes of a blood cell (e.g., red cells have the diameter around 7 {\mu}m). Whilst with present state-of-the-art in CMOS technology, this requirement in terms of size is currently un-feasible, recent research has advanced technology such that we can begin to work towards such an approach. Therefore, we present here the current limits of CMOS technology as well as the challenges related to the development of such a system. Towards this goal, this article presents the theoretical feasibility to obtain the first ever-conceived sub-10-um Bio/CMOS integrated circuit with biosensing capability to provide diagnostic telemetry once self-located in human tissue.
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PDF链接：
https://arxiv.org/pdf/1805.0584