Evidence map›Paper›PMID 36146247›Full record

ArticleSensors (Basel, Switzerland)2022

Vision-Based Performance Analysis of an Active Microfluidic Droplet Generation System Using Droplet Images.

Amith Mudugamuwa, Samith Hettiarachchi, Gehan Melroy, Shanuka Dodampegama, Menaka Konara, Uditha Roshan, Ranjith Amarasinghe, Dumith Jayathilaka, Peihong Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Periodic Flows in Microfluidics.Small (Weinheim an der Bergstrasse, Germany) · 2024
    Review
  2. Article
  3. 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

9 authors.

Amith MudugamuwaAccelerating Higher Education Expansion and Development (AHEAD) Project-Centre for Advanced Mechatronic Systems, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0002-1057-2374
Samith HettiarachchiAccelerating Higher Education Expansion and Development (AHEAD) Project-Centre for Advanced Mechatronic Systems, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0002-2103-1709
Gehan MelroyAccelerating Higher Education Expansion and Development (AHEAD) Project-Centre for Advanced Mechatronic Systems, University of Moratuwa, Katubedda 10400, Sri Lanka.
Shanuka DodampegamaAccelerating Higher Education Expansion and Development (AHEAD) Project-Centre for Advanced Mechatronic Systems, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0001-5323-7974
Menaka KonaraAccelerating Higher Education Expansion and Development (AHEAD) Project-Centre for Advanced Mechatronic Systems, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0002-7657-8488
Uditha RoshanDepartment of Mechanical Engineering, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0002-8543-1373
Ranjith AmarasingheAccelerating Higher Education Expansion and Development (AHEAD) Project-Centre for Advanced Mechatronic Systems, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0002-4960-4441
Dumith JayathilakaDepartment of Mechanical Engineering, University of Moratuwa, Katubedda 10400, Sri Lanka.ORCID 0000-0002-5130-6638
Peihong WangSchool of Physics and Materials Science, Anhui University, Hefei 230601, China.ORCID 0000-0001-6386-8446

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper discusses an active droplet generation system, and the presented droplet generator successfully performs droplet generation using two fluid phases: continuous phase fluid and dispersed phase fluid. The performance of an active droplet generation system is analysed based on the droplet morphology using vision sensing and digital image processing. The proposed system in the study includes a droplet generator, camera module with image pre-processing and identification algorithm, and controller and control algorithm with a workstation computer. The overall system is able to control, sense, and analyse the generation of droplets. The main controller consists of a microcontroller, motor controller, voltage regulator, and power supply. Among the morphological features of droplets, the diameter is extracted from the images to observe the system performance. The MATLAB-based image processing algorithm consists of image acquisition, image enhancement, droplet identification, feature extraction, and analysis. RGB band filtering, thresholding, and opening are used in image pre-processing. After the image enhancement, droplet identification is performed by tracing the boundary of the droplets. The average droplet diameter varied from ~3.05 mm to ~4.04 mm in the experiments, and the average droplet diameter decrement presented a relationship of a second-order polynomial with the droplet generation time.

Indexed as

Microfluidic Analytical TechniquesMicrofluidicsAlgorithmsactive droplet generationcomputer visiondroplet microfluidicsimage processinglab on a chipperformance analysis

Identifiers

PMID36146247
PMCPMC9503175

What OpenQuestion holds

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Registered trials

None linked

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.