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Home recording for pre-phase sleep apnea diagnosis by Holter recorder using MMC memory

机译:使用MMC存储器的Holter记录仪进行家庭记录以进行前期睡眠呼吸暂停诊断

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Long time data recordings by ambulatory devices became common today with widespread use of high capacity memories. In this study, this technology is used on home recording device especially designed for the pre-phase sleep apnea analysis at home before having certain diagnosis by proper polysomnographic examination in a hospital. Designing a portable recording system for clinically significant signals and analyzing an associated apnea detection algorithm are two significant and complementary studies carried out and reported in this paper. According to our aim, the Holter device discussed here is capable of recordings from many channels simultaneously but specifically for this study we consider just three signals namely ECG, breathing activity and oxygen saturation which are all significant for apnea detection in polysomnographic diagnostic phase. In apnea detection part we have initially studied the algorithm based on Hilbert Transform of ECG signal. The study also includes the comparison of three selected QRS detection algorithms (digital filter based, differentiation based and higher order statistics based) for ECG processing required for the Hilbert transform based apnea detection algorithm. Differentiation based QRS algorithm is preferred over other two due to its better performance on noisy ECG signals.
机译:长期以来,目前的数据录制是今天的常见,广泛使用高容量存储器。在这项研究中,该技术用于家庭记录装置,特别是为在医院中适当的多面经摄影检查进行了一定的诊断之前为家中的预阶段睡眠呼吸暂停分析设计。设计用于临床显着信号并分析相关的APNEA检测算法的便携式记录系统是在本文中进行的两个重要和互补的研究。根据我们的目的,这里讨论的Holter设备能够同时从许多频道记录,但专门为本研究我们认为只有三个信号,即ECG,呼吸活动和氧饱和度,这对于多陀螺诊断阶段的呼吸暂停检测都很重要。在APNEA检测部分中,我们最初研究了基于ECG信号的HILBERT变换的算法。该研究还包括比较三种所选QRS检测算法(基于数字滤波器,基于差分和高阶统计的基础),用于基于希尔伯特变换的APNEA检测算法所需的ECG处理。由于其在嘈杂的ECG信号上的更好性能,所以基于QRS算法优先于其他两个。

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