An Automated Tracking System for Movement Analysis of C. elegans

Abstract

C. elegans is one of the classic model organisms in neuroscience and biology, with its simple nervous system and transparent body serving as useful research tools. High-resolution imaging techniques allow for a detailed recording and analysis of C. elegans’ behaviors, such as locomotion, turning, probing, and jumping. These behaviors can be correlated with its neuronal activity and gene expression, thereby helping researchers understand the regulatory mechanisms of its behaviors and physiological processes. In this study, we propose an automated tracking system capable of rapidly and accurately collecting motion trajectory data of multiple C. elegans using skeletal extraction and SORT multi-object tracking algorithms. Furthermore, we introduce the use of Approximate Entropy to quantify the regularity and unpredictability of motion features, offering a novel approach for the analysis of C. elegans’ motion trajectories and movement features. This system also provides a convenient and automated tracking tool for related microorganism research fields.