COMPUTATION APPLIED TO CLINICAL EPILEPSY AND ANTIEPILEPTIC DEVICES
COMPUTATION APPLIED TO CLINICAL EPILEPSY AND ANTIEPILEPTIC DEVICES
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DOI：
10.1016/b978-012373649-9.50035-1
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发表时间：
2008-01-01
期刊：
影响因子：
--
通讯作者：
Litt, Brian
中科院分区：
文献类型：
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作者：
Echauz, Javier;Wong, Stephen;Litt, Brian
越来越多的计算神经科学家正在接受建立解剖学上准确的和临床相关的大脑功能网络模型的机会。这一趋势的一个强烈动机是将这项工作转化为临床诊断和治疗设备的场所激增。癫痫是转化神经工程中最活跃的领域之一，目前有两种早期设备处于关键临床试验中，其他一些设备紧随其后。本章中描述的用于临床翻译的方法并不是癫痫所独有的，而是来自工程、计算机科学和相关学科的不同领域。这些主题与其他工程领域的主题相似，包括用于工业应用的主题：处理条件信号（例如降噪），从系统中提取定量特征，训练和使用分类器执行决策任务，并根据分类器输出影响响应。在本章中，我们描述了几种方法，我们发现有用的检测，表征和跟踪癫痫发作及其在癫痫网络中的生成，并将其转化为临床设备。本章不是提供一个全面的参考，而是旨在传达一种方法和一个可以创造性地应用于手头任务的定量工具的样本。这项工作必须放在其他重要的相关任务的背景下，例如算法优化，硬件开发和临床翻译所需的植入式平台上的实施。就个人而言，本章还涉及“具有技术素养”的医生和工程师之间的多学科合作，他们对在我们生活的世界中发挥作用的技术进行建模、构建和部署。
More and more, computational neuroscientists are embracing opportunities to build anatomically accurate and clinically relevant models of functional networks in brain. One strong motivation for this trend is an explosion of venues for translating this work into clinical diagnostic and therapeutic devices. Epilepsy is one of the most active areas in translational neuroengineering, with two early devices currently in pivotal clinical trials, and a number of others close behind. The methods described in this chapter, used for this clinical translation, are not unique to epilepsy, but rather come from a collection of diverse fields in engineering, computer science and related disciplines. The themes are similar to those in other areas of engineering, including those used for industrial applications: condition signals for processing (e.g. noise reduction), extract quantitative features from the system, train and employ classifiers to perform decision tasks, and effect responses based upon classifier outputs. In this chapter, we describe several methods we have found useful for detecting, characterizing and tracking seizures and their generation in epileptic networks, and translating them into clinical devices. Rather than providing a comprehensive reference, this chapter is intended to convey an approach and a sampling of quantitative tools that can be creatively applied to the task at hand. This work must be put into the context of other important, related tasks, such as algorithm optimization, hardware development and implementation on implantable platforms that are required for clinical translation. On a personal note, this chapter is also about multidisciplinary collaboration between 'technically literate' physicians and engineers who model, build and deploy technologies that do things in the world we live in.