通过视觉感知:通过生物纳米物联网进行血液黏度的体内检测和外部传输

IF 4.3 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yue Sun;Kunlun Wu;Dong Du;Yifan Chen
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引用次数: 0

摘要

本研究通过生物纳米物联网(IoBNT)引入了一种新颖的“视觉感知”方法,用于实时体内检测和全血粘度(WBV)的外部传输。动机源于缺乏实时、无创技术来监测动态肿瘤诱导的生理变化。利用计算纳米生物传感(CONA)框架,我们将肿瘤靶向过程建模为一个自然计算问题,其中肿瘤触发的生物梯度场(BGFs)作为要优化的目标函数。外部控制的纳米群(NSs)充当搜索代理,感知BGF的变化,并将数据传输到外部监测设备。WBV是肿瘤微环境(tumor microenvironment, TME)的关键指标,调节NS动态,反映病理进展。我们采用NS空间分布的半最大值全宽度(FWHM)作为WBV估计的可测量参数,将对流扩散模型与统计力学相结合。为了解决测量噪声,我们提出了一种旋转磁场策略来稳定NS行为。在硅模拟中验证了毛细管尺度TME模型中WBV的时空动态,实现了10%的相对检测误差。我们的方法跟踪正弦、方形和三角形WBV波形,在热和流量变化下具有稳健的性能。与Brookfield粘度计测量值的强相关性(${R}^{{2}} ={0.9617}$)证实了经验一致性。研究结果证明了基于神经网络的闭环传感的可行性,推动了IoBNT在肿瘤检测和持续健康监测中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensing by Seeing: In Vivo Detection and External Transmission of Blood Viscosity Through the Internet of Bio-Nano Things
This study introduces a novel “sensing-by-seeing” methodology for real-time in vivo detection and external transmission of whole blood viscosity (WBV) through the Internet of Bio-Nano Things (IoBNT). The motivation arises from the lack of real-time, noninvasive techniques to monitor dynamic tumor-induced physiological changes. Leveraging the computational nanobiosensing (CONA) framework, we model the tumor targeting process as a natural computation problem, where tumor-triggered biological gradient fields (BGFs) serve as the objective function to be optimized. Externally controlled nanoswarms (NSs) act as search agents, sensing BGF variations, and transmitting data to an external monitoring device. WBV, a key indicator of the tumor microenvironment (TME), modulates NS dynamics and reflects pathological progression. We employ the full-width-at-half-maximum (FWHM) of NS spatial distributions as a measurable parameter for WBV estimation, integrating convection-diffusion modeling with statistical mechanics. To address measurement noise, we propose a rotating magnetic field strategy to stabilize NS behavior. In silico simulations validate the spatiotemporal dynamics of WBV in capillary-scale TME models, achieving a relative detection error of 10%. Our method tracks sinusoidal, square, and triangular WBV waveforms with robust performance under thermal and flow variations. A strong correlation ( ${R}^{{2}} = {0.9617}$ ) with Brookfield viscometer measurements confirms empirical consistency. The results demonstrate the feasibility of closed-loop NS-based sensing, advancing IoBNT applications in tumor detection and continuous health monitoring.
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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