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Single trial somatosensory evoked potential extraction with ARX filtering for a combined spinal cord intraoperative neuromonitoring technique

机译:单次试验体感诱发电位提取与ARX过滤结合脊髓术中神经监测技术

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Background When spinal cord functional integrity is at risk during surgery, intraoperative neuromonitoring is recommended. Tibial Single Trial Somatosensory Evoked Potentials (SEPs) and H-reflex are here used in a combined neuromonitoring method: both signals monitor the spinal cord status, though involving different nervous pathways. However, SEPs express a trial-to-trial variability that is difficult to track because of the intrinsic low signal-to-noise ratio. For this reason single trial techniques are needed to extract SEPs from the background EEG. Methods The analysis is performed off line on data recorded in eight scoliosis surgery sessions during which the spinal cord was simultaneously monitored through classical SEPs and H-reflex responses elicited by the same tibial nerve electrical stimulation. The single trial extraction of SEPs from the background EEG is here performed through AutoRegressive filter with eXogenous input (ARX). The electroencephalographic recording can be modeled as the sum of the background EEG, which can be described as an autoregressive process not related to the stimulus, and the evoked potential (EP), which can be viewed as a filtered version of a reference signal related to the stimulus. The choice of the filter optimal orders is based on the Akaike Information Criterion (AIC). The reference signal used as exogenous input in the ARX model is a weighted average of the previous SEPs trials with exponential forgetting behavior. Results The moving average exponentially weighted, used as reference signal for the ARX model, shows a better sensibility than the standard moving average in tracking SEPs fast inter-trial changes. The ability to promptly detect changes allows highlighting relations between waveform changes and surgical maneuvers. It also allows a comparative study with H-reflex trends: in particular, the two signals show different fall and recovery dynamics following stressful conditions for the spinal cord. Conclusion The ARX filter showed good performances in single trial SEP extraction, enhancing the available information concerning the current spinal cord status. Moreover, the comparison between SEPs and H-reflex showed that the two signals are affected by the same surgical maneuvers, even if they monitor the spinal cord through anatomically different pathways.
机译:背景技术当手术过程中脊髓功能完整性受到威胁时,建议进行术中神经监测。胫骨单试验体感诱发电位(SEPs)和H反射在此处用于组合的神经监测方法:两种信号均监测脊髓状态,尽管涉及不同的神经途径。但是,由于固有的低信噪比,SEP表示难以跟踪的试验间差异。因此,需要采用单一试验技术从背景脑电图中提取SEP。方法分析是在八个脊柱侧弯手术中记录的数据下进行的,在此过程中,通过经典的SEP和同一胫神经电刺激引起的H反射反应同时监测脊髓。通过带有外源输入(ARX)的自回归滤波器,可以从背景EEG中一次提取SEP。脑电图记录可以建模为背景EEG(可以描述为与刺激无关的自回归过程)和诱发电位(EP)的总和,可以将其视为与刺激。筛选器最佳顺序的选择基于Akaike信息准则(AIC)。在ARX模型中用作外源输入的参考信号是先前具有指数遗忘行为的SEP试验的加权平均值。结果用作ARX模型参考信号的指数加权移动平均值在跟踪SEP快速试验间变化方面显示出比标准移动平均值更好的敏感性。快速检测变化的能力可以突出显示波形变化与手术操作之间的关系。它还可以对H反射趋势进行比较研究:特别是,这两种信号在受压的脊髓条件下显示出不同的跌倒和恢复动力学。结论ARX过滤器在单次SEP提取中表现出良好的性能,增强了有关当前脊髓状态的可用信息。此外,SEP和H反射之间的比较表明,即使两个信号通过解剖学上不同的途径监测脊髓,它们也受相同的手术操作影响。

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