canaryTank: an in-tank husbandry behavior tracking system for health of fish facilities

canaryTank：用于鱼类设施健康的罐内饲养行为跟踪系统

• 批准号: 10453613
• 负责人: Pierre R. Martineau
• 金额: $ 18.95万
• 依托单位: MARTINEAU & ASSOCIATES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10453613
• 关键词: Address; Adopted; Adult; Aluminum; Animal Experimentation; Animal Model; Animal Technicians; Animals; Anxiety; Behavior; Behavior monitoring; Behavioral; Breeding; Coal; Code; Collection; Computer Vision Systems; Computer software; Custom; Darkness; Data; Detection; Development; Disease; Distress; Electronic Mail; Ensure; Environment; Ethics; Event; Exposure to; Fishes; Fostering; Funding; Future; Generations; Grant; Health; Health system; Healthcare; Human Resources; Hunger; Image; Imaging technology; Lasers; Light; Lighting; Maintenance; Measures; Medical Research; Methods; Monitor; Motion; Movement; Names; Neurosciences; Noise; Notification; Optics; Personal Satisfaction; Population; Positioning Attribute; Process; Pump; Reporter; Reporting; Research; Research Personnel; Research Project Grants; Saline; Secure; Sentinel; Serinus; Sleep; Specific qualifier value; Stream; System; Technology; Temperature; Testing; Text Messaging; Time; United States National Institutes of Health; Universities; Vision; Water; Zebrafish; automated algorithm; base; blind; bullying; cloud based; data standards; design; experimental study; feeding; fighting; human disease; human model; indexing; innovation; instrument; millisecond; neglect; operation; preservation; prototype; software infrastructure; success; temporal measurement; vibration; voltage; water quality; welfare

Project Summary/Abstract Zebrafish, involved in research projects totalling half a billion dollars of NIH funding in 2019, are the fastest growing animal model of human disease in medical research today. Thus, the health and wellbeing of medical research fish is paramount as the quality and robustness of experimental data depends on it. Innovation in zebrafish husbandry systems is crucially needed because current state-of-the-art non intrusive systems only track water quality measures. No commercial husbandry system has adopted automatic monitoring of fish behavior using video, despite the fact that most factors crucial in assessing fish health and well being, such as hunger, anxiety, or light changes, produce well known behavioral signatures that a computer vision system could detect. Because many such signatures require high temporal resolution, millisecond in the case of escape movements, video monitoring has been hampered by the need to process enormous data volumes. Here, the proposed effort aims at building a proof-of-concept system to video monitor a network of 10 custom tanks, codenamed “canaryTanks”, containing sentinel zebrafish populations strategically located in the racks of an existing fish facility. Each tank will be equipped with a custom illumination system and a camera that will use an original "Remanent Imaging" paradigm to capture and process orders of magnitude less data than standard video while preserving transient, millisecond-scale motion signatures. Threats to fish health—none of which are tracked by current commercial systems—will be detected through the real time analysis of motion signatures in the image streams captured by the canaryTanks and will be remotely accessible via browser through our cloud-based software infrastructure. The first aim is to show that such a system can generate timely and accurate daily reports of fish activity and sleep (actimetry), feeding times, and changes in room illumination based solely on processing the behavioral data in the images captured continuously by the canaryTanks. The second aim is to demonstrate the system’s ability to generate real-time alert notifications using custom algorithms that automatically detect a range of zebrafish behavioral signatures. A battery of tests, including disruption of the light cycle, exposure to noise/vibration and gradual increase to out-of-range temperatures, will validate this proof-of-concept. The future vision is that the canaryTank technology sets new standards in fish husbandry and provides revolutionary, ubiquitous in-tank recording capabilities that can be leveraged beyond husbandry for collection of experimental data.

项目概要/摘要 斑马鱼参与 2019 年 NIH 资助总额达 5 亿美元的研究项目，是最快的 当今医学研究中人类疾病动物模型的不断发展。因此，医疗保健和福祉 研究鱼至关重要，因为实验数据的质量和稳健性取决于它。创新于 斑马鱼饲养系统是至关重要的，因为目前最先进的非侵入式系统 跟踪水质措施。没有商业化饲养系统采用鱼类自动监测 尽管事实上大多数因素对于评估鱼类的健康和福祉至关重要，例如 饥饿、焦虑或光线变化会产生计算机视觉系统众所周知的行为特征 可以检测到。因为许多这样的签名需要高时间分辨率，在这种情况下是毫秒 在逃生行动中，视频监控因需要处理大量数据而受到阻碍。 这里，拟议的工作旨在构建一个概念验证系统来视频监控由 10 个自定义网络组成的网络 代号为“canaryTanks”的水箱，其中包含哨兵斑马鱼种群，战略性地分布在 现有的鱼类设施。每个坦克都将配备定制照明系统和摄像机 原始的“剩余成像”范例，用于捕获和处理比标准少几个数量级的数据 视频，同时保留瞬态、毫秒级的运动特征。对鱼类健康的威胁——没有一个 由当前的商业系统跟踪——将通过运动的实时分析来检测 canaryTanks 捕获的图像流中的签名可通过浏览器远程访问 通过我们基于云的软件基础设施。第一个目标是表明这样的系统可以生成 及时准确地每日报告鱼类活动和睡眠（活动测定）、喂食时间和房间变化 照明仅基于处理由连续捕获的图像中的行为数据 金丝雀坦克。第二个目标是展示系统生成实时警报通知的能力 使用自定义算法自动检测一系列斑马鱼的行为特征。一系列测试， 包括光周期中断、暴露于噪声/振动以及逐渐超出范围 温度，将验证这一概念验证。未来的愿景是canaryTank技术树立新的 鱼类饲养标准，并提供革命性的、无处不在的罐内记录功能，可以 利用畜牧业以外的方式收集实验数据。