Comparison of a micro-electro-mechanical system airflow sensor with the pneumotach in the forced oscillation technique

Design and Implementation of a Computer-Controlled Hybrid Oscillatory Ventilator

During mechanical ventilation, lung function and gas exchange in structurally heterogeneous lungs may be improved when volume oscillations at the airway opening are applied at multiple frequencies simultaneously, a technique referred to as multifrequency oscillatory ventilation (MFOV). This is in contrast to conventional high-frequency oscillatory ventilation (HFOV), for which oscillatory volumes are applied at a single frequency. In the present study, as a means of fully realizing the potential of MFOV, we designed and tested a computer-controlled hybrid oscillatory ventilator capable of generating the flows, tidal volumes, and airway pressures required for MFOV, HFOV, conventional mechanical ventilation (CMV), as well as oscillometric measurements of respiratory impedance. The device employs an iterative spectral feedback controller to generate a wide range of oscillatory waveforms. The performance of the device meets that of commercial mechanical ventilators in volume-controlled mode. Oscillatory modes of ventilation also meet design specifications in a mechanical test lung, over frequencies from 4 to 20 Hz and mean airway pressure from 5 to 30 cmH2O. In proof-of-concept experiments, the oscillatory ventilator maintained adequate gas exchange in a porcine model of acute lung injury, using combinations of conventional and oscillatory ventilation modalities. In summary, our novel device is capable of generating a wide range of conventional and oscillatory ventilation waveforms with potential to enhance gas exchange, while simultaneously providing less injurious ventilation.

Continuous Critical Respiratory Parameter Measurements Using a Single Low-Cost Relative Humidity Sensor: Evaluation Study

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.

Accurate Spirometry with Integrated Barometric Sensors in Face-Worn Garments

Cardiorespiratory (CR) signals are crucial vital signs for fitness condition tracking, medical diagnosis, and athlete performance evaluation. Monitoring such signals in real-life settings is among the most widespread applications of wearable computing. We investigate how miniaturized barometers can be used to perform accurate spirometry in a wearable system that is built on off-the-shelf training masks often used by athletes as a training aid. We perform an evaluation where differential barometric pressure sensors are compared concurrently with a digital spirometer, during an experimental setting of clinical forced vital capacity (FVC) test procedures with 20 participants. The relationship between the two instruments is derived by mathematical modeling first, then by various regression methods from experiment data. The results show that the error of FVC vital values between the two instruments can be as low as 2∼3%. Beyond clinical tests, the method can also measure continuous tidal breathing air volumes with a 1∼3% error margin. Overall, we conclude that barometers with millimeter footprints embedded in face mask apparel can perform similarly to a digital spirometer to monitor breathing airflow and volume in pulmonary function tests.