PDF(Pubmed)
Abstract：
BACKGROUND: Accurate and portable respiratory parameter measurements are critical for properly managing chronic obstructive pulmonary diseases (COPDs) such as asthma or sleep apnea, as well as controlling ventilation for patients in intensive care units, during surgical procedures, or when using a positive airway pressure device for sleep apnea.
OBJECTIVE: The purpose of this research is to develop a new nonprescription portable measurement device that utilizes relative humidity sensors (RHS) to accurately measure key respiratory parameters at a cost that is approximately 10 times less than the industry standard.
METHODS: We present the development, implementation, and assessment of a wearable respiratory measurement device using the commercial Bosch BME280 RHS. In the initial stage, the RHS was connected to the pneumotach (PNT) gold standard device via its external connector to gather breathing metrics. Data collection was facilitated using the Arduino platform with a Bluetooth Low Energy connection, and all measurements were taken in real time without any additional data processing. The device\'s efficacy was tested with 7 participants (5 men and 2 women), all in good health. In the subsequent phase, we specifically focused on comparing breathing cycle and respiratory rate measurements and determining the tidal volume by calculating the region between inhalation and exhalation peaks. Each participant\'s data were recorded over a span of 15 minutes. After the experiment, detailed statistical analysis was conducted using ANOVA and Bland-Altman to examine the accuracy and efficiency of our wearable device compared with the traditional methods.
RESULTS: The perfused air measured with the respiratory monitor enables clinicians to evaluate the absolute value of the tidal volume during ventilation of a patient. In contrast, directly connecting our RHS device to the surgical mask facilitates continuous lung volume monitoring. The results of the 1-way ANOVA showed high P values of .68 for respiratory volume and .89 for respiratory rate, which indicate that the group averages with the PNT standard are equivalent to those with our RHS platform, within the error margins of a typical instrument. Furthermore, analysis utilizing the Bland-Altman statistical method revealed a small bias of 0.03 with limits of agreement (LoAs) of -0.25 and 0.33. The RR bias was 0.018, and the LoAs were -1.89 and 1.89.
CONCLUSIONS: Based on the encouraging results, we conclude that our proposed design can be a viable, low-cost wearable medical device for pulmonary parametric measurement to prevent and predict the progression of pulmonary diseases. We believe that this will encourage the research community to investigate the application of RHS for monitoring the pulmonary health of individuals.
OBJECTIVE: The purpose of this research is to develop a new nonprescription portable measurement device that utilizes relative humidity sensors (RHS) to accurately measure key respiratory parameters at a cost that is approximately 10 times less than the industry standard.
METHODS: We present the development, implementation, and assessment of a wearable respiratory measurement device using the commercial Bosch BME280 RHS. In the initial stage, the RHS was connected to the pneumotach (PNT) gold standard device via its external connector to gather breathing metrics. Data collection was facilitated using the Arduino platform with a Bluetooth Low Energy connection, and all measurements were taken in real time without any additional data processing. The device\'s efficacy was tested with 7 participants (5 men and 2 women), all in good health. In the subsequent phase, we specifically focused on comparing breathing cycle and respiratory rate measurements and determining the tidal volume by calculating the region between inhalation and exhalation peaks. Each participant\'s data were recorded over a span of 15 minutes. After the experiment, detailed statistical analysis was conducted using ANOVA and Bland-Altman to examine the accuracy and efficiency of our wearable device compared with the traditional methods.
RESULTS: The perfused air measured with the respiratory monitor enables clinicians to evaluate the absolute value of the tidal volume during ventilation of a patient. In contrast, directly connecting our RHS device to the surgical mask facilitates continuous lung volume monitoring. The results of the 1-way ANOVA showed high P values of .68 for respiratory volume and .89 for respiratory rate, which indicate that the group averages with the PNT standard are equivalent to those with our RHS platform, within the error margins of a typical instrument. Furthermore, analysis utilizing the Bland-Altman statistical method revealed a small bias of 0.03 with limits of agreement (LoAs) of -0.25 and 0.33. The RR bias was 0.018, and the LoAs were -1.89 and 1.89.
CONCLUSIONS: Based on the encouraging results, we conclude that our proposed design can be a viable, low-cost wearable medical device for pulmonary parametric measurement to prevent and predict the progression of pulmonary diseases. We believe that this will encourage the research community to investigate the application of RHS for monitoring the pulmonary health of individuals.
摘要：
背景：准确和便携式的呼吸参数测量对于正确管理慢性阻塞性肺疾病（COPD）（如哮喘或睡眠呼吸暂停）至关重要，以及控制重症监护病房患者的通气，在手术过程中，或使用气道正压通气装置治疗睡眠呼吸暂停时。
目的：这项研究的目的是开发一种新型的非处方便携式测量设备，该设备利用相对湿度传感器（RHS）来精确测量关键的呼吸参数，其成本约为行业标准的10倍。
方法：我们介绍了发展，实施，并使用商用BoschBME280RHS评估可穿戴式呼吸测量设备。在初始阶段,RHS通过其外部连接器连接至bneuriotach(PNT)金标准装置,以收集呼吸指标.使用具有蓝牙低功耗连接的Arduino平台促进了数据收集，所有测量都是实时进行的，没有任何额外的数据处理。7名参与者（5名男性和2名女性）测试了该设备的功效，都身体健康。在随后的阶段,我们特别关注于比较呼吸周期和呼吸频率测量值,并通过计算吸气峰和呼气峰之间的区域来确定潮气量.每个参与者的数据在15分钟的时间内被记录。实验之后,使用ANOVA和Bland-Altman进行了详细的统计分析,以检验我们的可穿戴设备与传统方法相比的准确性和效率.
结果：使用呼吸监测器测量的灌注空气使临床医生能够评估患者通气期间潮气量的绝对值。相比之下,直接将我们的RHS设备连接到外科口罩，便于连续监测肺容量。单因素方差分析结果显示呼吸量为0.68,呼吸频率为0.89,这表明使用PNT标准的组平均值与使用我们的RHS平台的组平均值相当，在典型仪器的误差范围内。此外，利用Bland-Altman统计方法进行的分析显示，有0.03的小偏差，协议极限（LoAs）为-0.25和0.33。RR偏差为0.018，LoAs为-1.89和1.89。
结论：基于令人鼓舞的结果，我们得出结论，我们提出的设计可以是可行的，用于肺参数测量的低成本可穿戴医疗设备，以预防和预测肺部疾病的进展。我们相信，这将鼓励研究界研究RHS在监测个体肺部健康方面的应用。
目的：这项研究的目的是开发一种新型的非处方便携式测量设备，该设备利用相对湿度传感器（RHS）来精确测量关键的呼吸参数，其成本约为行业标准的10倍。
方法：我们介绍了发展，实施，并使用商用BoschBME280RHS评估可穿戴式呼吸测量设备。在初始阶段,RHS通过其外部连接器连接至bneuriotach(PNT)金标准装置,以收集呼吸指标.使用具有蓝牙低功耗连接的Arduino平台促进了数据收集，所有测量都是实时进行的，没有任何额外的数据处理。7名参与者（5名男性和2名女性）测试了该设备的功效，都身体健康。在随后的阶段,我们特别关注于比较呼吸周期和呼吸频率测量值,并通过计算吸气峰和呼气峰之间的区域来确定潮气量.每个参与者的数据在15分钟的时间内被记录。实验之后,使用ANOVA和Bland-Altman进行了详细的统计分析,以检验我们的可穿戴设备与传统方法相比的准确性和效率.
结果：使用呼吸监测器测量的灌注空气使临床医生能够评估患者通气期间潮气量的绝对值。相比之下,直接将我们的RHS设备连接到外科口罩，便于连续监测肺容量。单因素方差分析结果显示呼吸量为0.68,呼吸频率为0.89,这表明使用PNT标准的组平均值与使用我们的RHS平台的组平均值相当，在典型仪器的误差范围内。此外，利用Bland-Altman统计方法进行的分析显示，有0.03的小偏差，协议极限（LoAs）为-0.25和0.33。RR偏差为0.018，LoAs为-1.89和1.89。
结论：基于令人鼓舞的结果，我们得出结论，我们提出的设计可以是可行的，用于肺参数测量的低成本可穿戴医疗设备，以预防和预测肺部疾病的进展。我们相信，这将鼓励研究界研究RHS在监测个体肺部健康方面的应用。
