文献类型：期刊文献

英文题名：An intelligent multi-scale detection system for particle detection and automated splitting of particle-free droplets in digital microfluidic systems

作者：Guo, Kunlun[1];Dong, Juyue[1];Zhang, Junyu[1];Song, Zerui[1];Wang, Huifeng[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Meilong Rd 130, Shanghai 200237, Peoples R China

年份：2026

卷号：30

期号：5

外文期刊名：MICROFLUIDICS AND NANOFLUIDICS

收录：;EI(收录号：20261620508463);WOS:【SCI-EXPANDED(收录号:WOS:001739852700002)】；

基金：This research was funded by the National Key R&D Program of China (2023YFA1802000, 2024YFA0917700) and the National Natural Science Foundation of China (62103148) and the Shanghai Science and Technology Commission (contract number: 23141900900).

语种：英文

外文关键词：Digital microfluidics; Particle identification; Multi-scale object detection; Automated droplet splitting

摘要：Digital microfluidics (DMF) enable programmable manipulation of droplets, but the inevitable generation of microscopic particles necessitates the isolation of particle-free droplets for downstream analysis. Manual inspection is labor-intensive and impractical for high-throughput scales. We propose an integrated DMF system featuring a multi-scale object detection model based on YOLOv8 to achieve automated particle identification and droplet manipulation. Our model incorporates higher-resolution detection layers and an Efficient Local Attention module to overcome challenges posed by extreme scale differences and dense spatial distributions. Experimental results demonstrate that the model achieves a mean Average Precision (mAP@0.5) of 96.9% and a low counting error (MAE = 3.6) across various particle densities. Furthermore, we successfully implemented a real-time, visually guided workflow for automated splitting of particle-free droplets with a success rate of 94.0%. This system provides a robust foundation for automated quality control in high-throughput DMF-based biochemical assays.