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实时反馈驱动的单颗粒跟踪:综述与展望。

Real-Time Feedback-Driven Single-Particle Tracking: A Survey and Perspective.

机构信息

Department of Physics, University of Pretoria, Pretoria, 0002, South Africa.

Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, 0002, South Africa.

出版信息

Small. 2022 Jul;18(29):e2107024. doi: 10.1002/smll.202107024. Epub 2022 Jun 27.

Abstract

Real-time feedback-driven single-particle tracking (RT-FD-SPT) is a class of techniques in the field of single-particle tracking that uses feedback control to keep a particle of interest in a detection volume. These methods provide high spatiotemporal resolution on particle dynamics and allow for concurrent spectroscopic measurements. This review article begins with a survey of existing techniques and of applications where RT-FD-SPT has played an important role. Each of the core components of RT-FD-SPT are systematically discussed in order to develop an understanding of the trade-offs that must be made in algorithm design and to create a clear picture of the important differences, advantages, and drawbacks of existing approaches. These components are feedback tracking and control, ranging from simple proportional-integral-derivative control to advanced nonlinear techniques, estimation to determine particle location from the measured data, including both online and offline algorithms, and techniques for calibrating and characterizing different RT-FD-SPT methods. Then a collection of metrics for RT-FD-SPT is introduced to help guide experimentalists in selecting a method for their particular application and to help reveal where there are gaps in the techniques that represent opportunities for further development. Finally, this review is concluded with a discussion on future perspectives in the field.

摘要

实时反馈驱动的单粒子跟踪(RT-FD-SPT)是单粒子跟踪领域的一类技术,它使用反馈控制将感兴趣的粒子保持在检测体积内。这些方法在粒子动力学方面提供了高时空分辨率,并允许进行并发光谱测量。这篇综述文章首先调查了现有的技术以及 RT-FD-SPT 发挥重要作用的应用。为了深入了解算法设计中必须做出的权衡,并清楚地了解现有方法的重要差异、优势和缺点,我们系统地讨论了 RT-FD-SPT 的每个核心组件。这些组件包括反馈跟踪和控制,从简单的比例积分微分控制到先进的非线性技术,以及从测量数据中确定粒子位置的估计,包括在线和离线算法,以及用于校准和表征不同 RT-FD-SPT 方法的技术。然后,引入了一组用于 RT-FD-SPT 的指标,以帮助实验人员为其特定应用选择方法,并帮助揭示技术中存在差距的地方,这些差距代表了进一步发展的机会。最后,本文以对该领域未来展望的讨论结束。

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