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Cloudwave: Distributed Processing of Big Data from Electrophysiological Recordings for Epilepsy Clinical Research Using Hadoop

机译:Cloudwave:使用Hadoop进行癫痫临床研究的电生理记录中的大数据分布式处理

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摘要

Epilepsy is the most common serious neurological disorder affecting 50–60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical “big data” consisting of more than 100 multi-channel signals with recordings from each patient generating 5–10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a “private cloud”. Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with “montages” for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: )
机译:癫痫病是最常见的严重神经系统疾病,影响全世界50-60百万人。脑电图(EEG)和心电图(EKG)等多模式电生理数据对于有效的患者护理和癫痫的临床研究至关重要。电生理数据是临床“大数据”的一个示例,它由100多个多通道信号组成,每个患者的记录均产生5-10GB的数据。当前使用独立工具(例如Nihon Kohden神经病学软件)存储和分析信号数据的方法不足以满足日益增长的数据量以及支持通过实时和交互式访问支持多中心协作研究的需求。我们在本文中介绍Cloudwave平台,该平台具有基于Web的直观信号分析界面,该界面与基于Hadoop的数据处理模块集成在一起,该模块针对“私有云”中存储的临床数据实施。 Cloudwave已作为美国国家神经疾病和中风研究所(NINDS)资助的多中心SUDEP死亡率预防和风险识别(PRISM)项目的一部分而开发。 Cloudwave可视化界面提供带有“蒙太奇”的多模式信号的实时渲染,用于在Case大学医院癫痫监测单元生成的2TB患者数据上表征脑电图特征。 Cloudwave Hadoop数据处理模块的性能评估结果表明,在77GB的患者数据上,性能提高了一个数量级。 (Cloudwave项目:)

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