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Automated Testsystem of COGNISION(TM) Headset for Cognitive Diagnosis.

机译:用于认知诊断的COGNISION(TM)耳机自动化测试系统。

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摘要

There are more than 15 million Americans suffering from a chronic cognitive disability in the Unites States. Researchers have been exploring many different quantitative measures, such as event related potentials (ERP), electro-encephalogram (EEG), Magnetic Encephalogram (MEG) and Brain volumetry to accurately and repeatedly diagnose patients suffering from debilitating cognitive disorders. More than a million cases have been diagnosed every year, with many of those patients being misdiagnosed as a result of inadequate diagnostic and quality control tools. As a result, the medical device industry has been actively developing alternative diagnostic techniques, which implement one or more quantitative measures to improve diagnosis. For example, Neuronetrix (Louisville, KY) developed COGNISION(TM) that utilizes both ERP and EEG data to diagnose the cognitive ability of patients. The system has shown to be a powerful tool; however, its commercial success would be limited without lack of a fast and effective method of testing and validating the product. Thus, the goal of this study is to develop, test and validate a new "Testset" system for accurately and repeatedly validating the COGNISION(TM) Headset.;A Testset was constructed that is comprised of a software control component designed using the Labview G programming language, which runs on a computer terminal, a Data Acquisition (DAQ) card and switching board. The Testset is connected to a series of testing fixtures for interfacing with the various components of the Headset. The Testset evaluates the Headset at multiple stages of the manufacturing process as a whole system or by its individual components. At the first stage of production the Electrode Strings, amplifier board (Uberyoke), and Headset Control Unit (HCU) are tested and operated as individual printed circuit boards (PCBs). These components are again tested as mid-level assemblies and/or at the finished product stage as a complete autonomous system with the Testset monitoring the process. All tests are automated, requiring only a few parameters to be defined before a test is initiated by a single button press, and then selected test sequences are begun for that particular component or system and are completed in a few minutes.;A total of 2 Testsets were constructed and used to validate 10 Headsets. An automated software system was designed to control the Testset. The Testset demonstrated the ability to validate and test 100% of the individual components and completed assembled Headsets. The Testsets were found to be within 5% of the manufacturing specifications. Subsequently, the Automated Testset developed in this study enabled the manufacturer to provide a comprehensive report on the calibration parameters of the Headset, which is retained on file for each unit sold. The automated test system's statistical analysis shows that the two Testsets yielded reliable and consistent results with each other.
机译:在美国,有超过一千五百万的美国人患有慢性认知障碍。研究人员一直在探索许多不同的定量方法,例如事件相关电位(ERP),脑电图(EEG),磁脑图(MEG)和脑容量测定法,以准确并反复地诊断患有使人衰弱的认知障碍的患者。每年已诊断出超过一百万例病例,其中许多患者由于诊断和质量控制工具不足而被误诊。结果,医疗器械行业一直在积极开发替代性诊断技术,这些技术实施一种或多种定量措施以改善诊断。例如,Neuronetrix(肯塔基州路易斯维尔)开发了COGNISION™,该产品利用ERP和EEG数据来诊断患者的认知能力。该系统已被证明是功能强大的工具。但是,如果没有快速有效的产品测试和验证方法,其商业成功将受到限制。因此,本研究的目标是开发,测试和验证新的“ Testset”系统,以准确且反复地验证COGNISION(TM)耳机。;构建了一个Testset,该组件由使用Labview G设计的软件控制组件组成。在计算机终端,数据采集(DAQ)卡和交换板上运行的编程语言。测试仪连接到一系列测试夹具,用于与耳机的各个组件连接。测试仪在整个制造过程的多个阶段(整个系统或单个组件)评估耳机。在生产的第一阶段,对电极弦,放大器板(Uberyoke)和耳机控制单元(HCU)进行测试并作为单独的印刷电路板(PCB)进行操作。这些组件再次作为中级组件进行测试,并且/或者在成品阶段作为完整的自治系统进行测试,其中Testset监视过程。所有测试都是自动化的,只需按一次按钮即可启动测试,然后仅定义几个参数,然后针对该特定组件或系统开始选择的测试序列,并在几分钟内完成;总共2个测试集被构建并用于验证10个耳机。设计了一个自动化软件系统来控制测试仪。测试仪证明了能够验证和测试100%的单个组件以及完整的组装式耳机的能力。测试集被发现在制造规格的5%之内。随后,该研究中开发的自动测试仪使制造商能够提供有关耳机校准参数的全面报告,该报告将保存在每个销售单元的文件中。自动化测试系统的统计分析表明,这两个测试集彼此产生了可靠且一致的结果。

著录项

  • 作者

    White, Joshua I.;

  • 作者单位

    University of Louisville.;

  • 授予单位 University of Louisville.;
  • 学科 Engineering Biomedical.
  • 学位 M.Eng.
  • 年度 2013
  • 页码 203 p.
  • 总页数 203
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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