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Automatic Processing of Nasal Pressure Recordings to Derive Continuous Side-Selective Nasal Airflow and Conductance

机译:自动处理鼻压力记录以导出连续的侧选鼻气流和电导

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摘要

Monitoring of nasal airflow and conductance provides crucial insights into the variable nature of the nasal resistance, nasal cycle, and ventilation. We have previously shown that tracking of pressure swings at the entrance of each nasal passage by a dedicated catheter system allows bilateral monitoring of nasal airflow over several hours but requires complex linearization and calibration procedures. Side-selective nasal conductance is derived from linearized and calibrated bilateral nasal pressure swings and corresponding driving pressure, i.e., the transnasal pressure difference derived from an epipharyngeal catheter. Manual analysis of such recordings and computation of instantaneous conductance as the ratio of flow to driving pressure over several hours is extremely tedious, time consuming, and therefore not suitable for routine practice. To address this point, we developed and validated a software for automatic processing of nasal and epipharyngeal pressure recordings as a convenient tool for studying the nasal ventilation. The software applies an eight-parameter logistic model to transform nasal pressure swings into side-selective estimates of airflow that are calibrated and further processed along with epipharyngeal pressure to compute bilateral nasal conductance over consecutive, user-selectable time-segments. Essential processing steps include (1) offset correction, (2) low-pass filtering, (3) cross-correlation, (4) cutting of signals into individual breaths, (5) normalization, (6) ensemble averaging to obtain a mean pressure signal for each nasal side, (7) derivation of airflow, conductance, and further variables. Among four evaluated algorithms for calculation of nasal conductance, the derivative of the airflow-pressure curve according to the mean value theorem agreed closest with the gold standard, i.e., the conductance derived from airflow measured by a pneumotachograph attached to an oral-nasal mask and transnasal pressure. In combination with the nasal catheter system, our novel software represents a valuable tool for use in clinical practice and research to conveniently investigate nasal ventilation and its changes occurring spontaneously or in response to various exposures and therapeutic interventions.
机译:鼻气流和电导的监测为了解鼻阻力,鼻循环和通气的可变性质提供了重要的见识。先前我们已经表明,通过专用导管系统跟踪每个鼻腔通道入口处的压力波动,可以在几个小时内对鼻腔气流进行双向监测,但需要复杂的线性化和校准程序。侧向选择的鼻导度是从线性化和校准的双侧鼻腔压力波动和相应的驱动压力得出的,即从鼻咽导管得到的经鼻压差。手动分析此类记录并计算瞬时电导率(如几个小时内的流量与驱动压力之比)非常繁琐,耗时,因此不适合常规实践。为了解决这一问题,我们开发并验证了用于自动处理鼻和咽咽压力记录的软件,作为研究鼻通气的便捷工具。该软件应用八参数逻辑模型,将鼻压力波动转换为气流的侧向选择性估计值,并与上咽压力一起校准和进一步处理,以计算连续的,用户可选的时间段内的双侧鼻腔电导率。基本的处理步骤包括(1)偏移校正,(2)低通滤波,(3)互相关,(4)将信号切成单个呼吸,(5)归一化,(6)集合平均以获得平均压力每个鼻侧发出信号,(7)推导气流,电导率和其他变量。在用于评估鼻电导的四种评估算法中,根据平均值定理的气流压力曲线的导数与金标准最接近,即通过连接至鼻腔面罩的气动描记器测量的气流推导的电导率。经鼻压力。结合鼻导管系统,我们的新型软件代表了一种有价值的工具,可用于临床实践和研究,以方便地研究鼻通气及其自发发生的变化或对各种暴露和治疗干预的反应。

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