移动平台的新生儿EEG解释和决策支持框架
Neonatal EEG Interpretation and Decision Support Framework for Mobile Platforms
摘要：
本文提出并实现了一种直观且普遍的解决方案，用于在超声和深度学习AI的辅助下进行新生儿EEG监测，为所有新生儿医疗保健专业人员提供有关新生儿大脑健康的信息，特别是那些没有EEG解释专业知识的人。该系统旨在增加能够诊断新生儿EEG异常的临床医生的人口统计学。该系统采用低成本、低功耗的脑电采集系统。Android应用程序提供单通道EEG可视化、由经过训练的深度卷积神经网络提供的新生儿癫痫发作存在的交通灯指示以及EEG声化算法，旨在促进对新生儿癫痫发作特定EEG形态变化的感知。多方面的EEG解释框架，并实现了移动平台架构的功耗和准确性进行了分析。
英文摘要：
This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals, particularly those without EEG interpretation expertise. The system aims to increase the demographic of clinicians capable of diagnosing abnormalities in neonatal EEG. The proposed system uses a low-cost and low-power EEG acquisition system. An Android app provides single-channel EEG visualization, traffic-light indication of the presence of neonatal seizures provided by a trained, deep convolutional neural network and an algorithm for EEG sonification, designed to facilitate the perception of changes in EEG morphology specific to neonatal seizures. The multifaceted EEG interpretation framework is presented and the implemented mobile platform architecture is analyzed with respect to its power consumption and accuracy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
