Evidence map›Paper›PMID 36300161›Full record

ArticleIEEE transactions on control systems technology : a publication of the IEEE Control Systems Society2022

Synthetic Stochastic Motion Platform for Testing Single Particle Tracking Microscopes.

Nicholas A Vickers, Sean B Andersson

Abstract read
In one paragraph

Article in IEEE transactions on control systems technology : a publication of the IEEE Control Systems Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Real-Time Feedback-Driven Single-Particle Tracking: A Survey and Perspective.Small (Weinheim an der Bergstrasse, Germany) · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Nicholas A VickersDepartment of Mechanical Engineering, Boston University, Boston, MA, 02215 USA.ORCID 0000-0002-2293-9671
Sean B AnderssonDepartment of Mechanical Engineering and the Division of Systems Engineering, Boston University, Boston, MA, 02215 USA.ORCID 0000-0001-7575-3507

Funding

Joint estimation of motion model, model parameters, and particle trajectories in single particle trackingR01GM117039 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI ANDERSSON, SEAN B. · 2017 to 2021
$1.7M
NIGMS NIH HHS R01 GM117039
6 · The paper itself

Abstract

We describe the design and implementation of a control system for testing the performance of single particle tracking microscopes with the method of synthetic motion. Single particle tracking (SPT) has become a common and powerful tool in the study of biomolecular transport in cellular biology, providing the ability to track individual biological macromolecules in their native environment. Existing methods for testing SPT techniques rely on physical simulations and there is a clear need for experimental-based schemes for both comparing different approaches and for characterizing the accuracy and precision of techniques on particular experimental setups. Synthetic motion, that is, using an actuator such as a nanopositioning stage to drive a particle along a known ground-truth trajectory, is a means for achieving these ends. However, the resolution, accuracy, and flexibility of this method is limited by the actuator static and dynamic characteristics. In this work we apply system identification and model inverse feedforward control to increase actuator bandwidth and address some common actuator nonlinearities, develop a set of dimensionless numbers that describe system limitations, and provide a set of guidelines for the practical use of synthetic motion in SPT.

Indexed as

Feedforward ControlNonlinear SystemsPiezoelectric controlSingle Particle TrackingSystem Identification

Identifiers

PMID36300161
PMCPMC9590407

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.