Monitoring Daphnia magna heart rate provides significant potential as a sensitive physiological indicator for ecotoxicological assessment, yet its broader application has been limited by low-throughput, high variability, reliance on mean-based interpretation, and difficulties in analysing multiple individuals simultaneously. Here, we present an integrated methodology combining stress-minimised immobilisation, high-speed imaging, and Fourier-based analysis to monitor 150 individuals per hour. This high-throughput system enables distribution- and probability-based statistical analysis rather than conventional mean-based approaches. Using kernel density estimation and Gaussian deconvolution, multimodal cardiac response patterns and unrecognised subpopulations were identified. Distribution-based convergence analysis revealed stable estimation at N ≥ 63 (σ = 26.36 bpm; R² = 0.89), supporting N = 100 as a statistically robust sample size. Application to reference substances, such as hydrogen peroxide and caffeine validated the method for detecting chemically induced cardiac alterations. Additional exposure to paraquat and potassium dichromate revealed dose-dependent heart rate alterations below EC 50 levels. Copper oxide nanoparticles induced abnormal elevation below EC 10 , and gold nanoparticles caused irregular distributions (~ 31.2%) below no observed effect concentration. These results demonstrate the improved sensitivity, reproducibility, and ecological relevance, offering a rapid, non-invasive, and probabilistic tool for early detection of sublethal stress in next-generation environmental risk assessment. • The platform tracks heart rate in 150 daphnids per hour with high precision • Large-scale heart rate data enabled probabilistic analysis beyond mean-based method • The method detects responses at concentrations far below test guideline levels • This method enables evaluation of pollutants that cause early physiological change
Kwon et al. (Wed,) studied this question.