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Novel Method for Synchronization of Multiple Biosensors

机译:多种生物传感器同步的新方法

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Synchronization of signals in the post-trial analysis is a laborious process that is often a bottleneck during the signal analysis. As the concept of the Internet-of-Things (IoT) emerges and more sensors are implemented in a research trial, reliable synchronization schemes are becoming increasingly important. This article presents a synchronization algorithm that could align signals recorded by different platforms with different sampling frequencies to millisecond-level precision. The algorithm could also realign a recording that has been restarted after a device failure with the same alignment precision as the rest of the signals. The algorithm generates a secondary signal by permutation of six different step voltages in each cycle to produce a unique pattern before returning to a baseline. The algorithm has been deployed in an actual clinical trial involving 26 heart failure patients and five different bio-signal modalities. It has successfully aligned all trials, including one trial that had a device failure during the recording. Two aligned heart signals had an average beat-to-beat interval difference of 0.81 ± 0.79 ms or 0.90 ± 0.87% with no sign of a negative effect of the synchronization algorithm.
机译:试验后分析中信号的同步是一种费力的过程,其通常是信号分析期间的瓶颈。随着物联网的概念(IOT)出现和更多传感器在研究试验中实施,可靠的同步方案变得越来越重要。本文介绍了一个同步算法,可以将不同平台记录的信号与不同的采样频率对齐至毫秒精度。该算法还可以重新录制一记录,该记录已经在设备故障和其余信号的其余部分相同的对准精度之后重新启动。算法通过每个循环中的六个不同的阶跃电压的置换产生辅助信号,以在返回基线之前产生唯一的图案。该算法已在实际临床试验中部署,涉及26例心力衰竭患者和五种不同的生物信号模式。它已成功对齐所有试验,包括在录制过程中具有设备故障的一个试验。两个对齐的心脏信号平均搏动间隔差0.81±0.79ms或0.90±0.87%,没有同步算法的负面影响的迹象。

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