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青鳉鱼的行为特征提取研究

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刘翠棉, 饶凯锋, 李婧, 唐亮, 裴琨, 谷金峰, 刘勇, 王伟, 姜杰, 马梅, 王子健. 青鳉鱼的行为特征提取研究[J]. 生态毒理学报, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
引用本文: 刘翠棉, 饶凯锋, 李婧, 唐亮, 裴琨, 谷金峰, 刘勇, 王伟, 姜杰, 马梅, 王子健. 青鳉鱼的行为特征提取研究[J]. 生态毒理学报, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
shu
Liu Cuimian, Rao Kaifeng, Li Jing, Tang Liang, Pei Kun, Gu Jinfeng, Liu Yong, Wang Wei, Jiang Jie, Ma Mei, Wang Zijian. Behavior Feature Extraction Based on Medaka[J]. Asian journal of ecotoxicology, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
Citation: Liu Cuimian, Rao Kaifeng, Li Jing, Tang Liang, Pei Kun, Gu Jinfeng, Liu Yong, Wang Wei, Jiang Jie, Ma Mei, Wang Zijian. Behavior Feature Extraction Based on Medaka[J]. Asian journal of ecotoxicology, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
shu

青鳉鱼的行为特征提取研究

  • 1. 石家庄市环境监控中心, 石家庄 050000;

  • 2. 中国科学院生态环境研究中心, 环境模拟与污染控制国家重点联合实验室, 北京 100085;

  • 3. 中国科学院生态环境研究中心, 中国科学院饮用水科学与技术重点实验室, 北京 100085;

  • 4. 石家庄市环境综合执法支队, 石家庄 050000;

  • 5. 无锡中科水质环境技术有限公司, 无锡 214024;

  • 6. 中国科学院大学资源与环境学院, 北京 101407

    • 作者简介: 刘翠棉(1974-),女,硕士,研究方向为环境监测,E-mail:liuxinyi9911@126.com
  • 基金项目:

    国家重点研发计划资助项目(2019YFD0901100)；后勤科研重大项目(AWS18J004)；中国科学院前沿科学重点研究项目(QYZDY-SSW-DQC004)；广东省省级科技计划项目(2016B02024007)

  • 中图分类号: X171.5

Behavior Feature Extraction Based on Medaka

  • 1. Shijiazhuang Environmental Monitoring Center, Shijiazhuang 050000, China;

  • 2. State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;

  • 3. Key Laboratory of Drinking Water Science and Technology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;

  • 4. Shijiazhuang Environmental Comprehensive Law Enforcement Detachment, Shijiazhuang 050000, China;

  • 5. CASA (Wuxi) Environmental Technology Co. Ltd., Wuxi 214024, China;

  • 6. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 101407, China

  • Fund Project:

  • 摘要: 采用生物行为传感器获取青鳉鱼的行为数据时，青鳉鱼个体差异会导致采集到的原始电信号在时空特性下完全不同。重要的行为特征往往被隐藏在原始信号中，传统的信号处理方法无法实时而有效地提取到这些特征。针对这个问题，观察并记录了暴露实验前后青鳉鱼的行为变化，提出了一种可以高效表征行为特征的直方图统计算法。实验结果表明，该方法能够准确对应人眼观测到的暴露实验前后鱼的行为变化趋势，同时也为后续异常行为识别提供一定的支持和参考。
    Abstract: When biological behavioral sensors were used to obtain the behavior data of the medaka, the individual differences of the medaka would cause the original electrical signals collected to be completely different under the temporal and spatial characteristics. Important behavioral features are often hidden in the original signal, traditional signal processing methods cannot effectively extract these features in real time. In this view, we observe and record the changes in the behavior of the medaka before and after the exposure experiment, and propose a histogram statistics algorithm, in order to effectively characterize the behavioral characteristics of the medaka. The experimental results show that this method can accurately reflect the changes before and after the exposure experiment observed by human eyes, and it also provides some support and reference for subsequent abnormal behavior identification.
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  • 收稿日期:  2018-07-16
刘翠棉, 饶凯锋, 李婧, 唐亮, 裴琨, 谷金峰, 刘勇, 王伟, 姜杰, 马梅, 王子健. 青鳉鱼的行为特征提取研究[J]. 生态毒理学报, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
引用本文: 刘翠棉, 饶凯锋, 李婧, 唐亮, 裴琨, 谷金峰, 刘勇, 王伟, 姜杰, 马梅, 王子健. 青鳉鱼的行为特征提取研究[J]. 生态毒理学报, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
shu
Liu Cuimian, Rao Kaifeng, Li Jing, Tang Liang, Pei Kun, Gu Jinfeng, Liu Yong, Wang Wei, Jiang Jie, Ma Mei, Wang Zijian. Behavior Feature Extraction Based on Medaka[J]. Asian journal of ecotoxicology, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
Citation: Liu Cuimian, Rao Kaifeng, Li Jing, Tang Liang, Pei Kun, Gu Jinfeng, Liu Yong, Wang Wei, Jiang Jie, Ma Mei, Wang Zijian. Behavior Feature Extraction Based on Medaka[J]. Asian journal of ecotoxicology, 2020, 15(2): 160-170. doi: 10.7524/AJE.1673-5897.20180716001
shu

青鳉鱼的行为特征提取研究

    作者简介: 刘翠棉(1974-),女,硕士,研究方向为环境监测,E-mail:liuxinyi9911@126.com
  • 1. 石家庄市环境监控中心, 石家庄 050000;
  • 2. 中国科学院生态环境研究中心, 环境模拟与污染控制国家重点联合实验室, 北京 100085;
  • 3. 中国科学院生态环境研究中心, 中国科学院饮用水科学与技术重点实验室, 北京 100085;
  • 4. 石家庄市环境综合执法支队, 石家庄 050000;
  • 5. 无锡中科水质环境技术有限公司, 无锡 214024;
  • 6. 中国科学院大学资源与环境学院, 北京 101407
  • 收稿日期:  2018-07-16
基金项目:

国家重点研发计划资助项目(2019YFD0901100)；后勤科研重大项目(AWS18J004)；中国科学院前沿科学重点研究项目(QYZDY-SSW-DQC004)；广东省省级科技计划项目(2016B02024007)

摘要: 采用生物行为传感器获取青鳉鱼的行为数据时，青鳉鱼个体差异会导致采集到的原始电信号在时空特性下完全不同。重要的行为特征往往被隐藏在原始信号中，传统的信号处理方法无法实时而有效地提取到这些特征。针对这个问题，观察并记录了暴露实验前后青鳉鱼的行为变化，提出了一种可以高效表征行为特征的直方图统计算法。实验结果表明，该方法能够准确对应人眼观测到的暴露实验前后鱼的行为变化趋势，同时也为后续异常行为识别提供一定的支持和参考。

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