Breath Detection Research Articles

Mask interfaces and devices for home noninvasive ventilation in children.

Home noninvasive ventilation (NIV), including continuous (CPAP) and bilevel (BPAP) positive airway pressure, is increasingly used in children worldwide. In this narrative review, we present a comprehensive summary of the equipment available for home NIV in pediatrics, excluding neonates. NIV may be challenging in young children, as the majority of the equipment has been developed for adults. Regarding the interfaces, only a few masks have been specifically developed for young children in recent years, while older children may benefit from a large variety of interfaces. Even though much progress has been made, skin injuries are still present, and need to be managed rapidly. Several studies addressed the management of the side effects, but recent studies are lacking regarding orofacial anomalies. No recent study reported the available interfaces for young children and the strategies for an optimal mask fit. Regarding the devices, an adapted NIV device to pediatrics that allows an adequate patient's breathing detection should guarantee optimal ventilatory efficiency and monitoring of NIV. A close follow-up and regular monitoring should be mandatory to rule out the potential issues, optimize NIV therapy and ascertain the efficacy of NIV. However, studies are lacking to guide the choice of devices in young children and the optimal management of home NIV in pediatrics. We summarized the characteristics of the different interfaces available for young children and the limitations of NIV devices. We finally addressed potential areas for future research on long-term home NIV in children.

A fast response humidity sensor based on MXene-SWCNTs for the monitoring of respiration

Two-dimensional materials have attracted great interest in humidity sensing due to their excellent sensitivity and response time. Herein, we propose a humidity sensor consisting of MXene and single-walled carbon nanotubes (SWCNTs), using the Marangoni effect to self-assemble two-dimensional materials on the liquid surface, and then preparing them on the interdigital substrate through the layer-by-layer dip-coating method. Due to the expanded interlayer spacing of MXene and more exposed hydrogen active sites provided by SWCNTs, the sensor showed an excellent dynamic property with the response and recovery time of 2 s and 1.75 s Besides, the sensitivity is 0.53 pF/% RH (10–60% RH) and 7.6 pF/% RH (60–90% RH), the maximum humidity hysteresis is 6% of full scale (60% RH), and the reproducibility is ＞200cycles. Then, a flexible humidity breathing detection system has been developed based-on the sensor. Result demonstrated that it can detect human respiration and be successfully used to distinguish different human respiratory patterns. This work not only optimizes the dynamic property of sensors, but also provides a solution for the production of high-performance flexible humidity monitoring systems on this basis.

UV-promoted NH3 sensor based on Ti3C2Tx/TiO2/ graphene sandwich structure with ultrasensitive RT sensing performances for human health detection

Gases produced by human respiration can effectively forewarn physiological health, and developing high-performance gas sensors for breath detection can help in the early diagnosis of many diseases. In this paper, Ti3C2Tx/TiO2/graphene composite with a unique sandwich structure was fabricated by hydrothermal method for resistive NH3 sensor, which is composed of the staggered interlayer of graphene, Ti3C2Tx, and in situ grown TiO2 nanosheets. The results indicate that the Ti3C2Tx/TiO2/graphene composite sensor has a response value of 35.8 at 50 ppm NH3 at room temperature and in a dark environment, which is 12.8 times higher than that of the single Ti3C2Tx and can detect dilute NH3 at ppb level with a calculated limit of 26 ppb. The sensor also possesses a fast response/recovery time of 19/29 s and excellent humidity resistance. Furthermore, with the assistance of UV illumination, the sensor response value for 50 ppm NH3 is increased to 45.18, the response/recovery time is accelerated to 18/25 s, and the calculated limit of detection is 22.23 ppb. Additionally, simulated breath detection demonstrates the potential application of the sensor for early respiratory warning in patients with renal failure. Finally, the NH3 gas sensing mechanism is discussed in terms of heterogeneous structure, morphology promotion, and energy band theory. It is believed that the sensing material with this structure has great potential for human health applications.

Improving Breath Detection From Pulsed-Flow Oxygen Sources Using a New Nasal Interface.

Patients with COPD and other lung diseases are treated with long-term oxygen therapy (LTOT). Portable oxygen sources are required to administer LTOT while maintaining patient autonomy. Existing portable oxygen equipment has limitations that can hinder patient mobility. A novel nasal interface is presented in this study, aiming to enhance breath detection and triggering efficiency of portable pulsed-flow oxygen devices, thereby improving patient mobility and independence. To examine the effectiveness of the new interface, 8 respiratory therapists participated in trials using different oxygen sources (tank with oxygen-conserving device, SimplyGo Mini portable oxygen concentrator [POC], and OxyGo NEXT POC) and breathing types (nasal and oral) while using either the new nasal interface or a standard cannula. Each trial was video recorded so participant breaths could be retroactively matched with a pulse/no-pulse response, and triggering success rates were calculated by dividing the number of oxygen pulses by the number of breaths in each trial. After each trial, volunteers were asked to rate their perceived breathing resistance. Nasal breathing consistently resulted in higher triggering success rates compared to oral breathing for pulsed-flow oxygen devices. POCs exhibited higher triggering success rates than did the oxygen tanks with conserving device. However, there were no significant differences in triggering success rates between the two POC models. The new nasal interface demonstrated improved triggering success rates compared to the standard cannula. Whereas the new nasal interface was associated with a slight increase in perceived breathing resistance during nasal breathing trials, participants reported manageable resistance levels when using the interface. This study demonstrates that the new nasal interface can improve triggering success rates of pulsed-flow oxygen devices during both nasal and oral breathing scenarios. Further research involving patient trials is recommended to understand the clinical implications of improved pulse triggering.

Ru-Doped MoS2 Monolayer for Exhaled Breath Detection on Early Lung Cancer Diagnosis: A First-Principles Investigation.

Nanosensor-based patient exhaled breath detection is a practical and effective way to detect lung cancer early. In this paper, a Ru-doped MoS2 monolayer (Ru-MoS2) is proposed as a promising novel biosensor based on first-principles theory for the detection of three typical early stage lung cancer exhaled volatile organic compounds, namely, C3H4O, C3H6O, and C5H8. Replacement of a S atom in the MoS2 monolayer with a Ru dopant atom to form a stable Ru-MoS2 monolayer with a binding energy of -4.78 eV is further demonstrated by the thermostability and chemical stability analysis as well as improving the adsorption performance of the system for three VOCs. The adsorption configuration structures, adsorption properties, and electronic behavior of the Ru-MoS2 monolayer are investigated by electron deformation density and density of states analysis to gain a comprehensive understanding of the physicochemical properties as sensing material. The results show that the adsorption energies of the Ru-MoS2 monolayer for C3H4O, C3H6O, and C5H8 are 3.42, -1.53, and -2.80 eV, respectively, all of which are chemisorption with excellent adsorption performance. The sensitivities for the three VOCs could be up to 1.09, 140.50, and 5.90, respectively, and the band structure and work function further elucidate the sensing mechanism of the Ru-MoS2 monolayer as a resistive gas sensor. The type and concentration of these exhaled breaths may reflect changes in the patient's physiological and biochemical status and may serve as a probe for the diagnosis of lung cancer. The results in this work could provide a guidance for researchers to explore the practical applications in the early diagnosis of lung cancer by gas sensors.

Ultralow-hysteresis quartz crystal microbalance humidity sensor based on electrospinned cellulose acetate/konjac glucomannan network-like film

There are numerous and significant uses for accurate and reliable humidity detection in day-to-day living. In this study, a QCM humidity sensor based on cellulose acetate/konjac glucomannan (CA/KGM) film was constructed. The elemental composition, morphology and nanostructure of the film were characterized using scanning electron microscopy (SEM), water contact angle tester, X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FT-IR). The CA/KGM QCM humidity sensor exhibited excellent stability, selectivity and repeatability with low humidity hysteresis and short response/recovery time (12.3 s/0.1 s). The experimental results show that the introduction of CA in KGM can dramatically improve the mechanical properties and stability of the composite membrane. The humidity sensing mechanism of the sensor was systematically investigated, and water droplet counting test, fingertip moisture detection and human breath detection were performed. The sensor offers a wide range of potential applications.

1D/2D Heterostructured WS2@PANI Composite for Highly Sensitive, Flexible, and Room Temperature Ammonia Gas Sensor.

Flexible and room-temperature (RT) ammonia gas sensors are needed for exhaled breath detection and recognition. Two-dimensional transition metal disulfides are potential materials for RT gas sensing because of their low band gap and a large number of edge-exposed sites that can provide strong binding to gas molecules. In this work, a 1D/2D heterostructured composite material of 2D tungsten disulfide (WS2) modified with 1D polyaniline (PANI) was proposed. The fibrous PANI adsorbed on the edges and inserted in the interlayers of the laminated WS2 provide more diffusion channels for the ammonia gas and act as sensing sites. The WS2@PANI-based sensor shows high selectivity for ammonia with satisfying reproducibility and long-term stability. A response of 216.3% and a short response/recovery time of 25 s/39 s were achieved for 100 ppm ammonia gas. The sensing mechanism was investigated in detail via complex impedance spectra and in situ FT-IR, which was attributed to the synergistic effect of WS2 and PANI. The excellent sensing performance coupled with its resistance to thermal and humidity interference endows the WS2@PANI-based sensor with potential for human exhaled detection and wearable electronics.

Airflow-Induced Flexoelectric Bending Sensors for Human Breath Detection

Airflow-Induced Flexoelectric Bending Sensors for Human Breath Detection

The effect of high ethanol concentration on E-nose response for diabetes detection in exhaled breath: Laboratory studies

The growing number of people with diabetes has paved the way for the creation of non-invasive devices to measure blood glucose levels and enable the detection of diabetes non-invasively, for example, through exhaled air. This paper presents the development of a breath detection system using multiple sensors (e-nose system) for the non-invasive estimation of blood glucose levels. The system employs commercially available ethanol, CO2, and acetone sensors, with synthetic breath mixtures used for testing, including four scenarios with high ethanol concentrations (0–570 ppm) as an influence factor. Results showed a mean absolute error of 0.245 ppm when analysing commonly observed acetone concentrations in diabetic breath using four sensors and the XGBoost Regressor. In mixtures with high ethanol concentrations and varying acetone concentrations (0–8.62 ppm), the CatBoost Regressor outperformed other machine learning algorithms with a mean absolute error of 0.568 ppm. This study emphasises the significant impact of ethanol on acetone detection and the need to consider ethanol levels in the developing of non-invasive devices for blood glucose prediction based on the exhaled acetone measurements. The research shows that a set of three gas sensors is optimal for estimating acetone concentrations in gas mixtures. The presented results constitute a preliminary step towards developing a non-invasive device for estimating blood glucose levels based on breath analysis, with the novelty of considering alcohol intake as a potential influencing factor.

SERS-Based Hydrogen Bonding Induction Strategy for Gaseous Acetic Acid Capture and Detection.

Surface-enhanced Raman scattering (SERS) can overcome the existing technological limitations, such as complex processes and harsh conditions in gaseous small-molecule detection, and advance the development of real-time gas sensing at room temperature. In this study, a SERS-based hydrogen bonding induction strategy for capturing and sensing gaseous acetic acid is proposed for the detection demands of gaseous acetic acid. This addresses the challenges of low adsorption of gaseous small molecules on SERS substrates and small Raman scattering cross sections and enables the first SERS-based detection of gaseous acetic acid by a portable Raman spectrometer. To provide abundant hydrogen bond donors and acceptors, 4-mercaptobenzoic acid (4-MBA) was used as a ligand molecule modified on the SERS substrate. Furthermore, a sensing chip with a low relative standard deviation (RSD) of 4.15% was constructed, ensuring highly sensitive and reliable detection. The hydrogen bond-induced acetic acid trapping was confirmed by experimental spectroscopy and density functional theory (DFT). In addition, to achieve superior accuracy compared to conventional methods, an innovative analytical method based on direct response hydrogen bond formation (IO-H/Iref) was proposed, enabling the detection of gaseous acetic acid at concentrations as low as 60 ppb. The strategy demonstrated a superior anti-interference capability in simulated breath and wine detection systems. Moreover, the high reusability of the chip highlights the significant potential for real-time sensing of gaseous acetic acid.

Alternative electrolyte solutions for untargeted breath metabolomics using secondary-electrospray ionization high-resolution mass spectrometry.

Secondary-electrospray ionization (SESI) coupled with high-resolution mass spectrometry is a powerful tool for the discovery of biomarkers in exhaled breath. A primary electrospray consisting of aqueous formic acid (FA) is currently used to charge the volatile organic compounds in breath. To investigate whether alternate electrospray compositions could enable different metabolite coverage and sensitivities, the electrospray dopants NaI and AgNO3 were tested. In a proof-of-principle manner, the exhaled breath of one subject was analyzed repeatedly with different electrospray solutions and with the help of a spectral stitching technique. Capillary diameter and position were optimized to achieve proper detection of exhaled breath. The detected features were then compared using formula annotation. Using an evaporation-based gas standard system, the signal response of the different solutions was probed. Principal component analysis revealed a substantial difference in features detected with AgNO3 . With silver, more sulfur-containing features and more unsaturated hydrocarbon compounds were detected. Furthermore, more primary amines were potentially ionized, as indicated by van Krewelen diagrams. In total, twice as many features were unique to AgNO3 than for other electrospray dopants. Using gas standards at known concentrations, the high sensitivity of FA as a dopant was demonstrated but also indicated alternate sensitivities of the other electrospray solutions. This work demonstrated the potential of AgNO3 as a complementary dopant for further biomarker discovery in SESI-based breath analysis.

BreathFinder: A Method for Non-Invasive Isolation of Respiratory Cycles Utilizing the Thoracic Respiratory Inductance Plethysmography Signal.

The field of automatic respiratory analysis focuses mainly on breath detection on signals such as audio recordings, or nasal flow measurement, which suffer from issues with background noise and other disturbances. Here we introduce a novel algorithm designed to isolate individual respiratory cycles on a thoracic respiratory inductance plethysmography signal using the non-invasive signal of the respiratory inductance plethysmography belts. The algorithm locates breaths using signal processing and statistical methods on the thoracic respiratory inductance plethysmography belt and enables the analysis of sleep data on an individual breath level. The algorithm was evaluated against a cohort of 31 participants, both healthy and diagnosed with obstructive sleep apnea. The dataset consisted of 13 female and 18 male participants between the ages of 20 and 69. The algorithm was evaluated on 7.3 hours of hand-annotated data from the cohort, or 8782 individual breaths in total. The algorithm was specifically evaluated on a dataset containing many sleep-disordered breathing events to confirm that it did not suffer in terms of accuracy when detecting breaths in the presence of sleep-disordered breathing. The algorithm was also evaluated across many participants, and we found that its accuracy was consistent across people. Source code for the algorithm was made public via an open-source Python library. The proposed algorithm achieved an estimated 94% accuracy when detecting breaths in respiratory signals while producing false positives that amount to only 5% of the total number of detections. The accuracy was not affected by the presence of respiratory related events, such as obstructive apneas or snoring. This work presents an automatic respiratory cycle algorithm suitable for use as an analytical tool for research based on individual breaths in sleep recordings that include respiratory inductance plethysmography.

Pristine and aurum-decorated tungsten ditellurides as sensing materials for VOCs detection in exhaled human breath: DFT analysis.

In this research, we employed density functional theory (DFT) to evaluate the sensing capabilities of transition metal-decorated two-dimensional WTe2 TMDs nanosheets toward VOCs such as (acetone, ethanol, methanol, toluene, and formaldehyde) that are exhaled in human breath and can serve as potential biomarkers for detecting specific physiological disorders and also gases interfering in exhaled breath (CO2 and H2O) detection. Au can be physically decorated onto the surface of WTe2. We analyzed the density of states (DOS), adsorption energy, charge transfer, and sensing behavior. The pristine WTe2 monolayer, exhibiting a semiconductor characteristic with a band gap of 0.63 eV, transitions to a metallic state upon Au-decoration, due to its actively stable nature and promising negative adsorption energy value, it triggers the emergence of novel states within the DOS. Computed adsorption energies of VOCs range from -0.08 to -0.57 eV, with greater interaction distances confirming the physisorption behavior of these VOCs biomarkers on Au-WTe2. Ethanol displays greater sensitivity compared to other considered VOCs. Au-WTe2 exhibits promising potential as a viable option for detecting VOCs in breath analysis applications at room temperature, owing to its excellent adsorption capabilities and sensitivity. Overall, our results highlight aurum-decorated tungsten ditelluride's potential as an efficient nano-sensor for detecting VOCs associated with early-stage lung cancer diagnoses.

Skin Conductance Response Artifact Reduction: Leveraging Accelerometer Noise Reference and Deep Breath Detection

Skin Conductance Response Artifact Reduction: Leveraging Accelerometer Noise Reference and Deep Breath Detection

Volatile organic compounds in cancer and exhaled breath detection technology.

The detection of volatile organic compounds (VOCs) in breath has become a potential method for early cancer screening. Although this approach has attracted increasing attention from the both scientific and medical communities, it has not received appreciable traction in the clinical setting. There are two main obstacles. One involves the identification of specific biomarkers or combinations thereof especially in early cancer. The other is the lack the specialized equipment for breath analysis having the appropriate sensitivity and specificity. Using metabolomics, this chapter examines the research strategies involving gas biomarkers in cancer patient breath, cancer cell gas metabolites and synthetic biomarkers. We briefly explore gas biomarkers of seven cancers and introduce principles of detection and clinical application. Large analytical instruments and small sensor technology are highlighted. Challenges to VOC analysis are presented including clinical use, extraction and detection, miniaturization efforts and examination of metabolic VOC pathways. Finally, VOCs in cancer and in exhaled breath detection technology are summarized and future prospects explored.

Mixed Potential Type Acetone Sensor with Ultralow Detection Limit for Diabetic Ketosis Breath Analysis.

Breath analysis using gas sensors is an emerging method for disease screening and diagnosis. Since it is closely related to the lipid metabolism and blood ketone concentration of the body, the detection of acetone content in exhaled breath is helpful for the screening and monitoring of diabetes and ketosis. The development of an acetone sensor with high selectivity, stability, and low detection limit has been the research focus for this purpose. Here, we developed a mixed potential type acetone sensor based on Gd2Zr2O7 solid electrolyte and CoSb2O6 sensing electrode. The developed sensor exhibits an extremely low detection limit of 10 ppb, enabling linear detection for acetone in an extremely wide range of 10 ppb-100 ppm. The good results of systematic evaluation on selectivity, repeatability, and stability prove the superior reliability of the sensor, which is a prerequisite for the application in actual breath detection. The ability of the sensor to distinguish healthy people from diabetic ketosis patients was confirmed by using the sensor to detect the breath of healthy people and diabetic patients, proving the feasibility of the sensor in the diagnosis and monitoring of diabetic ketosis.

2D Ti3C2Tx-MXene nanosheets and graphene oxide based highly sensitive humidity sensor for wearable and flexible electronics

To explore the potential of Ti3C2Tx-MXenes as an electrode over traditional metals, we designed a high-performance and cost-effective humidity sensor using 2D Ti3C2Tx MXene nanosheets (TMNSs) as electrodes and Graphene oxide (GO) as a sensing layer. The sensor was fabricated on a flexible and transparent Cyclic Olefin Copolymer (COC) substrate using UV-photolithography, spin coating, and spray coating techniques. Electrical impedance measurements demonstrated the sensor's remarkable sensitivity to humidity, with a response range of 6 % to 97 % at frequencies of 1 kHz and 10 kHz. The sensor exhibited fast response and recovery times of 0.8 s and 0.9 s, respectively, and maintained stable performance over 24 h. We further employed DFT simulations to establish the atomic level understanding of humidity sensing. The findings demonstrated the presence of a physical bond between the hydrogen (H) and oxygen (O) atoms, which are part of the water molecule and OH group, respectively, in the process of humidity sensing. Furthermore, the OH-configuration of graphene oxide (GO) acts as the main active site in humidity sensing, outperforming the O-configuration, due to its higher adsorption energy and charge transfer. Moreover, real-world applications for this 2D materials-based sensor were demonstrated, including non-contact proximity sensing and human breathing detection, demonstrating its potential. This study makes a substantial contribution to the development of low-cost humidity sensors based on 2D materials, with implications for a wide range of humidity sensing applications.

Quantum mechanisms for selective detection in complex gas mixtures using conductive sensors

In this paper, we consider new quantum mechanisms for selective detection in complex gaseous media which provide the highest possible efficiency of quantum sensors and for the first time analyze their nature. On the basis of these quantum mechanisms, the concepts of quantum detection and innovative methods of analysis are developed, which are virtually impossible to implement in the conventional conductive sensors and nanosensors. Examples of original solutions to problems in the field of detection and analysis of human breath using point-contact sensors are considered. A new method of analysis based on detection of metastable quantum states of the "point-contact sensor—breath" system in dynamic mode is proposed. The conductance histogram of dendritic Yanson point contacts recorded for this system is a unique energy signature of breath which allows differentiation between the states of human body. We demonstrate that nanosized Yanson point contacts, which, thanks to their quantum properties, can replace a massive spectrometer, open up wide opportunities for solving complex problems in the field of breath analysis using a new generation of portable high-tech quantum sensor devices.

Random Body Movement Interference Mitigation in Radar Breath Detection Based on L1 Norm

Random Body Movement Interference Mitigation in Radar Breath Detection Based on L1 Norm

Noncontact Respiratory Motion Detection in Anesthetized Rodents.

Small animal physiology studies are often complicated, but the level of complexity is greatly increased when performing live-animal X-ray imaging studies at synchrotron radiation facilities. This is because these facilities are typically not designed specifically for biomedical research, and the animals and image detectors are located away from the researchers in a radiation enclosure. In respiratory X-ray imaging studies one challenge is the detection of respiration in free-breathing anaesthetised rodents, to enable images to be acquired at specific phases of the breath and for detecting changes in respiratory rate. We have previously used a Philtec RC60 sensor interfaced to a PowerLab data acquisition system and custom-designed timing hub to perform this task. Here we evaluated the Panasonic HL-G108 for respiratory sensing. The performance of the two sensors for accurate and reliable breath detection was directly compared using a single anesthetized rat. We also assessed how an infrared heat lamp used to maintain body temperature affected sensor performance. Based on positive results from these comparisons, the HL-G108 sensor was then used for respiratory motion detection in tracheal X-ray imaging studies of 21 rats at the SPring-8 Synchrotron, including its use for gated image acquisition. The results of that test were compared to a similar imaging study that used the RC60 for respiratory detection in 19 rats. Finally, the HL-G108 sensor was tested on 5 mice to determine its effectiveness on smaller species. The results showed that the HL-G108 is much more robust and easier to configure than the RC60 sensor and produces an analog signal that is amenable to stable peak detection. Furthermore, gated image acquisition produced sequences with substantially reduced motion artefacts, enabling the additional benefit of reduced radiation dose through the application of shuttering. Finally, the mouse experiments showed that the HL-G108 is equally capable of detecting respiration in this smaller species.