Environmental stressors such as water pollution, temperature fluctuations, and dissolved oxygen depletion significantly impact the physiology and behavior of aquatic organisms. Among physiological indicators, heart rate is one of the most immediate and sensitive biomarkers of stress and can serve as a reliable proxy for environmental health. In this study, we present a novel, non-invasive method for monitoring the heart rate of small transparent fish using video imaging and motion analysis techniques, without the need for electrodes, anesthesia, or restraint.

We conducted experiments using Danionella translucida, a genetically unmodified, naturally transparent teleost fish with a clearly visible cardiovascular system. High-frame-rate video recordings were analyzed using frame-differencing and luminance-based motion detection to extract cardiac pulsations from the heart region. The estimated heart rate was validated against manual annotations, showing consistent agreement with less than 5% error across multiple trials. The system demonstrated a robust performance in detecting subtle changes in heart rate under varying environmental conditions, including temperature changes and exposure to low levels of chemical contaminants.

Our technique is cost-effective, accessible, and well suited to long-term in vivo monitoring, making it applicable not only in laboratory experiments but also in aquaculture and environmental surveillance. Furthermore, we discuss the potential of integrating this system with AI-based anomaly detection and remote sensing platforms to create a scalable, real-time water quality monitoring solution. These findings highlight the utility of fish cardiac physiology as a biological sensor and offer a new pathway for linking individual-level stress responses to broader ecological and environmental health indicators.