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: 7250940
• 负责人: YIQING LIANG
• 金额: $ 51.84万
• 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/7250940
• 关键词: Adverse effects; Algorithms; Animals; Area; Behavioral; Behavioral Research; Body part; Cavia; Chemicals; Class; Classification; Classification Scheme; Clinical; Clonus; Colorado; Communities; Complement; Computer Analysis; Computer Architectures; Computer Systems; Computers; Coupled; Data; Detection; Electrical Engineering; Electroencephalography; Epilepsy; Exhibits; Forelimb; Gene Mutation; Genes; Genotype; Guinea; Human; Mastication; Medical; Medicine; Minor; Monitor; Motion; Movement; Mus; Mutant Strains Mice; Myoclonic Epilepsies; National Institute of Drug Abuse; National Institute of Mental Health; Numbers; Oral cavity; Patients; Pattern; Pharmaceutical Preparations; Phase; Phenotype; Posture; Process; Purpose; Range; Rate; Rattus; Research; Research Institute; Resolution; Rodent; Scheme; Screening procedure; Security; Seizures; Signal Transduction; Solutions; Stream; Susceptibility Gene; System; Systems Integration; Tail; Technology; Testing; Time; Today; Training; Transgenic Organisms; Universities; Validation; Video Recording; Visual; Wolves; Work; base; college; design; digital; experience; high throughput screening; improved; interest; mouse model; preclinical study; professor; prototype; rapid growth; research study; tool; volunteer

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）：我们建议开发一个功能完整的原型系统，用于动物（主要是小鼠或大鼠或豚鼠）基于符号学（视频记录）的自动化和高通量癫痫发作检测和分类。该项目的目的是，首先开发能够通过目视观察自动检测缉获情况的技术和工具;然后在可能的情况下根据一种分类办法对这些缉获情况进一步分类。视频检测和分类方法将补充EEG分析方法，以实现准确和精确的结果。这些检测和分类将以高通量模式进行，以满足日益增长的需求。该技术将为癫痫发作的检测和分析开辟一条除传统的发作期癫痫样（intal epileptiform，EEG）记录分析之外的新途径，可大大提高啮齿类动物癫痫发作的检测和分类结果，为癫痫研究提供一种极为有力的工具。这项技术还将提高质量，减轻观察啮齿动物癫痫发作的负担，并实现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的系统集成等领域的研究。我们将利用我们在过去的DARPA项目和我们目前的NIMH和NIDA项目中开发的数字视频处理和分析技术。