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Electrowetting-based Digital Microfluidics Platform for Automated Enzyme-linked Immunosorbent Assay

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Published on: February 23, 2020

Artificial intelligence-enabled multipurpose smart detection in active-matrix electrowetting-on-dielectric digital

Zhiqiang Jia^1,2,3, Chunyu Chang^2,3, Siyi Hu^2,3

¹College of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun, Jilin Province, 130022, PR China.

Microsystems & Nanoengineering

|September 26, 2024

Summary

This study introduces an AI-enabled smart detection system for active-matrix electrowetting-on-dielectric (AM-EWOD) platforms. The system enhances automated biochemical reactions and droplet manipulation for lab-on-a-chip applications.

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Last Updated: Jun 12, 2025

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Published on: September 19, 2017

Area of Science:

Biotechnology
Microfluidics
Artificial Intelligence

Background:

Active-matrix electrowetting-on-dielectric (AM-EWOD) systems enable complex on-chip biochemical reactions through precise droplet manipulation.
A smart detection system is crucial for automating workflows and enabling online programming in AM-EWOD systems.

Purpose of the Study:

To demonstrate an artificial intelligence (AI)-enabled multipurpose smart detection method for AM-EWOD systems.
To enhance the automation and efficiency of on-chip biochemical reactions and droplet manipulation.

Main Methods:

Utilized the U-Net model for quantitative evaluation of droplet-splitting uniformity.
Employed the YOLOv8 model for online monitoring of droplet-splitting processes.
Developed an improved YOLOv8 model for detecting single-cell samples in nanolitre droplets.

Main Results:

Achieved a 97.76% droplet-splitting success rate across 18 AM-EWOD chips.
Obtained high model precision (99.982%) and recall (99.980%) for droplet splitting.
Reached 99.260% precision and 99.193% recall for single-cell detection, with demonstrated sorting and routing capabilities.

Conclusions:

The AI-based smart detection system significantly improves the reliability and automation of AM-EWOD platforms.
This integrated system shows substantial potential for realizing true lab-on-a-chip applications.