journal article·2025-06-23Open access

Heart Rate Monitoring System for Fish Larvae Using Interframe Luminance Difference

Emi Yuda, Naoya Morikawa, Yutaka Yoshida, Yasuhito Shimada

Applied Sciences· Volume 15· Issue 13

Abstract

Danionella, a transparent freshwater species belonging to the Cyprinidae family, has emerged as a valuable model organism in biological and medical research due to its optical transparency. The cardiovascular system of Danionella larvae provides a unique opportunity for non-invasive heart rate monitoring in aquatic animals. Traditional approaches for evaluating larval heart rate often require manual or semi-automated definition of the cardiac region in video recordings. In this study, we developed a simplified heart rate monitoring system that estimates heartbeat activity by analyzing interframe luminance differences in video sequences of Danionella larvae. Our system successfully measured heart rates in the range of 150–155 beats per minute (bpm), consistent with previous findings reporting rates between 140 and 200 bpm. The non-invasive nature of this method offers significant advantages for high-throughput screening and long-term physiological monitoring. Furthermore, this system has potential applications in evaluating environmental stressors, supporting survival and health assessments, and guiding habitat management strategies to ensure stable populations of adult fish in both natural and laboratory settings.
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Research context

OpenAlex topics: Water Quality Monitoring Technologies · Advanced Chemical Sensor Technologies · Neurobiology and Insect Physiology Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Innovation Center for Semiconductor and Digital Future, Mie University, Tsu 514-0102, Japan

Department of Management Science and Technology, School of Engineering, Tohoku University, Sendai 980-8577, Japan

School of Engineering, Mie University, Tsu 514-0102, Japan

Graduate School of Design and Architecture, Nagoya City University, Nagoya 464-0083, Japan

Department of Integrative Pharmacology, Graduate School of Medicine, Mie University, Tsu 514-0102, Japan

Zebrafish Research Center, Mie University, Tsu 514-0102, Japan

References (32)

Show source-provided references
1. Chan, P.K., Lin, C.C., and Cheng, S.H. (2009). Noninvasive technique for measurement of heartbeat regularity in zebrafish (Danio rerio) embryos. BMC Biotechnol., 9.10.1186/1472-6750-9-11 ↗
2. Denvir, M.A., Tucker, C.S., and Mullins, J.J. (2008). Systolic and diastolic ventricular function in zebrafish embryos: Influence of norepinephrine, MS-222 and temperature. BMC Biotechnol., 8.10.1186/1472-6750-8-21 ↗
3. A new method for detection and quantification of heartbeat parameters in Drosophila, zebrafish, and embryonic mouse hearts10.2144/000113078 ↗
4. Influence of hypoxia and of hypoxemia on the development of cardiac activity in zebrafish larvae10.1152/ajpregu.00673.2001 ↗
5. Danionella fishes10.1038/s41592-024-02433-0 ↗
6. Longitudinal in vivo imaging of adult Danionella cerebrum using standard confocal microscopy10.1242/dmm.049753 ↗
7. Transparent Danionella translucida as a genetically tractable vertebrate brain model10.1038/s41592-018-0144-6 ↗
8. Lindemann, N., Kalix, L., Possiel, J., Stasch, R., Kusian, T., Köster, R.W., and von Trotha, J.W. (2022). A comparative analysis of Danionella cerebrum and zebrafish (Danio rerio) larval locomotor activity in a light-dark test. Front. Behav. Neurosci., 16.10.3389/fnbeh.2022.885775 ↗
9. Zhang, H., Wei, Z., Wu, D., Dai, Z., Hughes, D., Sugahara, T., Izumi, S., and Yang, Y. (2024, January 20–23). Flexible, Non-Invasive, and Wearable Fish Heart Rate Monitoring Tag for Guiding Aquaculture in Marine Ranching. Proceedings of the 2024 IEEE SENSORS, Kobe, Japan.10.1109/SENSORS60989.2024.10785047 ↗
10. In-Situ Fish Heart-Rate Estimation and Feeding Event Detection Using an Implantable Biologger10.1109/TMC.2021.3086496 ↗
11. Shen, Y., Arablouei, R., de Hoog, F., Malan, J., Sharp, J., Shouri, S., Clark, T.D., Lefevre, C., Kroon, F., and Severati, A. (2020, January 21–24). Estimating Heart Rate and Detecting Feeding Events of Fish Using an Implantable Biologger. Proceedings of the 2020 ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Sydney, Australia.10.1109/IPSN48710.2020.00-48 ↗
12. Puybareau, É., Talbot, H., and Léonard, M. (2015, January 10–13). Automated heart rate estimation in fish embryo. Proceedings of the 2015 International Conference on Image Processing Theory, Tools and Applications (IPTA), Orleans, France.10.1109/IPTA.2015.7367171 ↗
13. Real-time detection of workload changes using heart rate variability10.1016/j.bspc.2011.07.004 ↗
14. An Efficient Time-Varying Filter for Detrending and Bandwidth Limiting the Heart Rate Variability Tachogram without Resampling: MATLAB Open-Source Code and Internet Web-Based Implementation10.1155/2012/578785 ↗
15. The Ornstein-Uhlenbeck Third-Order Gaussian Process (OUGP) Applied Directly to the Un-Resampled Heart Rate Variability (HRV) Tachogram for Detrending and Low-Pass Filtering10.1007/s11517-012-0928-2 ↗
16. Influence of Melatonin on the Immune System of Fish: A Review10.3390/ijms14047979 ↗
17. Nutrigenomics and Immune Function in Fish: New Insights from Omics Technologies10.1016/j.dci.2017.02.024 ↗
18. Necropsy-Based Wild Fish Health Assessment
19. Microbial Manipulations to Improve Fish Health and Production—A Mediterranean Perspective10.1016/j.fsi.2010.08.009 ↗
20. Fish Health—Some Concepts, Constraints, and Comparisons10.1111/j.1749-6632.1975.tb26826.x ↗
21. Functional Amino Acids in Fish Nutrition, Health, and Welfare
22. Health of Farmed Fish: Its Relation to Fish Welfare and Its Utility as Welfare Indicator10.1007/s10695-011-9517-9 ↗
23. Maintenance of Fish Health in Aquaculture: Review of Concepts and Challenges
24. Fish health management in aquaculture
25. Nutrition and Health of Aquaculture Fish10.1111/j.1365-2761.2011.01333.x ↗
26. Kang, C.-P., Tu, H.-C., Fu, T.-F., Wu, J.-M., Chu, P.-H., and Chang, D.T.-H. (2018). An Automatic Method to Calculate Heart Rate from Zebrafish Larval Cardiac Videos. BMC Bioinform., 19.10.1186/s12859-018-2166-6 ↗
27. Ensembled YOLO for Multiorgan Detection in Chest X-Rays
28. MedYOLO: A Medical Image Object Detection Framework10.1007/s10278-024-01138-2 ↗
29. Image-Decomposition-Enhanced Deep Learning for Detection of Rotor Cores in Cardiac Fibrillation10.1109/TBME.2023.3292383 ↗
30. BEEHIVE: A Dataset of Apis mellifera Images to Empower Honeybee Monitoring Research10.1016/j.dib.2024.111055 ↗
31. The Application of Emotion Valence Ratios in Facial Emotion Recognition for Detecting Depression Among Older Adults in Institutional Settings
32. Kim, Y.S., Kim, J.G., Choi, H.Y., Lee, D., Kong, J.W., Kang, G.H., Jang, Y.S., Kim, W., Lee, Y., and Kim, J. (2024). Detection of Aortic Dissection and Intramural Hematoma in Non-Contrast Chest Computed Tomography Using a You Only Look Once-Based Deep Learning Model. J. Clin. Med., 13.10.3390/jcm13226868 ↗