Digital Video Monitor and Analysis of Seizures with EEG

数字视频监测和脑电图癫痫发作分析

• 批准号: 7069608
• 负责人: YIQING LIANG
• 金额: $ 52.98万
• 依托单位: CLEVER SYSTEMS, INC.
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2008-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7069608
• 关键词: behavioral /social science research tag; bioimaging /biomedical imaging; bioterrorism /chemical warfare; brain disorder diagnosis; brain electrical activity; computer assisted diagnosis; computer program /software; convulsions; diagnosis design /evaluation; disease /disorder classification; disease /disorder model; electroencephalography; epilepsy; ethology; gene mutation; guinea pigs; high throughput technology; laboratory mouse; laboratory rat; neuropsychology; species difference; video recording system

DESCRIPTION (PROVIDED BY APPLICANT): we propose to develop a completely functioning prototype system for automated and high-throughput seizure detection and classification in animals, mainly in mice or rats or guinea pigs, based on semiology (video record). The purposes of the project are to first develop technologies and tools that can automatically detect seizures through visual observation; then further classify those seizures according to a classification scheme when possible. The video detection and classification approach will complement EEG analysis approach to achieve accurate and precise results. These detection and classification will be conducted in high throughput mode to meet the increasing demand. This technology will open a new avenue to detecting and analyzing seizures besides traditional ictal epileptiform (EEG) recording analysis, and can greatly improve the results of detection and classification of seizures in rodents, thus providing an extremely powerful tool in epilepsy research. This technology will also improve the quality and alleviate the burden of observing rodents' seizures and achieve more objective and consistent analysis. The technology will also contribute to homeland security for chemical defense. For this purpose, this project will include studies in the areas of behavioral research, epilepsy and seizure observation and analysis, computer algorithm design, as well as complete system integration. We will make use of the technologies for digital video processing and analysis that we have developed with past DARPA projects and our current NIMH and NIDA projects.

描述（由申请人提供）：我们建议开发一个完全运行的原型系统，用于基于符号学（视频记录），用于动物的自动化和高通量癫痫发作检测和分类。该项目的目的是首先开发可以通过视觉观察自动检测癫痫发作的技术和工具。然后在可能的情况下根据分类方案进一步对这些癫痫发作进行分类。视频检测和分类方法将补充脑电图分析方法，以实现准确而准确的结果。这些检测和分类将在高通量模式下进行以满足日益增长的需求。这项技术将为检测和分析癫痫发作外的癫痫发作（EEG）记录分析开辟新的途径，并可以大大改善啮齿动物中癫痫发作的检测和分类的结果，从而为癫痫研究提供了极为强大的工具。该技术还将提高质量，并减轻观察啮齿动物癫痫发作的负担，并进行更客观和一致的分析。该技术还将有助于化学防御的国土安全。为此，该项目将包括在行为研究，癫痫和癫痫发作观察和分析，计算机算法设计以及完整系统集成方面的研究。我们将利用过去DARPA项目以及当前的NIMH和NIDA项目开发的数字视频处理和分析技术。