CPAP Pressure and Flow Data from a Local Trial of 30 Adults at the University of Canterbury

A pressure and flow dataset for CPAP (continuous positive airway pressure) breathing obtained from 30 subjects for model-based identification of patient-specific lung mechanics using a specially designed sensor system comprising an array of differential pressure sensors (Sensirion AG SDP816-125PA) and gauge pressure sensors (NXP MPVZ4006GW7U). Relevant medical information was collected using a questionnaire, including: sex; age; weight; height; smoking history; and history of asthma. Subjects were tasked with breathing at five different rates (including passive) from very slow to very fast breathing, matched to an online pacing sound and video, at two different levels of CPAP (4 and 7 cmH2O) for between 50 and 180 seconds depending on rate. Each data set for a breathing rate comprises ~17 breaths, including rest periods between breathing rates and CPAP levels. Data with significant observed sensor error was removed during processing. A better-fitted mask would be expected to reduce error in fully capturing expiration by reducing leaks around the masks seal with the face. The sensors measure inspiration and expiration using separate unidirectional differential flow sensors, which are combined in post-processing to for complete breathing data.

本数据集由30名受试者提供，用于基于模型的病人特异性肺力学识别，数据来源于持续气道正压（CPAP）呼吸过程中的压力和流量。该数据集通过一个特别设计的传感器系统收集，该系统包括差分压力传感器阵列（Sensirion AG SDP816-125PA）和压力计式压力传感器（NXP MPVZ4006GW7U）。通过问卷调查收集了相关的医学信息，包括性别、年龄、体重、身高、吸烟史和哮喘病史。受试者被要求以五级不同的呼吸速率（包括被动呼吸）从极慢到极快进行呼吸，呼吸速率与在线节拍声和视频同步，CPAP压力设置为两个不同水平（4和7 cmH2O），持续时间根据呼吸速率在50至180秒之间。每个呼吸速率的数据集包含约17次呼吸，包括呼吸速率和CPAP压力水平之间的休息期。在数据处理过程中，移除了具有显著传感器误差的数据。预期更好的适配面罩将减少由于面罩与面部密封处的泄漏而导致的完全捕捉呼气的误差。传感器通过使用单独的定向差分流量传感器测量吸气量和呼气量，这些传感器在后续处理中合并以形成完整的呼吸数据。