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基于双核处理器的新生儿脑功能监护仪的研制

Development of cerebral function monitor in the neonate based on dual-core processor

作者: 张山根  叶大田  彭诚 
单位:                      清华大学深圳研究生院生物医学工程研究中心(深圳518055)        
关键词:                     新生儿脑功能监护仪;嵌入式;振幅整合脑电图;样本熵          
分类号:
出版年·卷·期(页码):2014·33·6(627-635)
摘要:

           目的  目前市场上的新生儿脑功能监护仪多为国外研发生产,多采用单导脑电和振幅整合脑电图算法,价格昂贵、体积庞大。为了实现降低成本、小型化和多评估参数的目的,研发了一款具有低成本、小型化、多评估参数、丰富操作功能和友好用户界面特点的新生儿脑功能监护系统。 方法  首先该系统第一部分基于DSP&ARM双核处理器及QT工具,设计并搭建了嵌入式开发平台,其中硬件部分基于A/D、单片机和DSP&ARM双核处理平台OMAPL138开发板,实现了信号的采集、存储、处理和实时显示等功能。其次,移植了振幅整合脑电图(amplitude-integrated electroencephalography, aEEG)和样本熵(sample entropy , SampEn)两种算法,完成了基于Linux操作系统对开发平台的控制软件。然后基于Qt开发工具设计并搭建了新生儿脑功能监护仪用户平台,平台包括患者信息管理系统、波形显示系统、数据标注系统和数据标注数据库等模块。 结果  经过系统整体调试和测试,仪器能够实现aEEG和SampEn多参数评估,实时床旁监测病情等功能。 结论  基于双核处理器技术研发的脑功能监护仪能够实现低成本、小型化、多评估参数、丰富操作功能和友好用户界面的目的,达到了预期目标。    

       Objective The mainly cerebral function monitors in the neonate are developed aboard, with the feathers of high cost, only one parameter and large volume. This paper reports a cerebral function monitoring system in the neonate, with the feathers of low cost, miniaturization, multi evaluation parameters, rich functions and friendly user interface. Methods Firstly we designed and built the embedded development platform based on the DSP&ARM dual core processor and the tool of Qt. Based on A/D converter, microcontroller and the dual core professor platform OMAPL138, the hardware realized the functions of signal acquisition, data storage, data processing and real-time display for waveform. The system transplanted the two algorithms of aEEG and SampEn, and completed the control software of the development platform based on Linux Operating System. Then based on the tool of Qt, we built the user platform of the cerebral function monitor in the neonate, including the models of the patient information management system, waveform display system, data annotation system and data annotation database. Results After being debugged and tested, the device had the function of multi evaluation parameters of aEEG and SampEn, and real-time monitoring. Conclusions This cerebral function monitor in the neonate based on dual-core processor reaches the expected aim of low cost, miniaturization, multi evaluation parameters, rich functions and friendly user interface.

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