Breath Sensor Research Articles

Fast and ultrasensitive breath sensors based on biamine-functionalized graphene oxide

Fast and ultrasensitive breath sensors based on biamine-functionalized graphene oxide

A Wearable Breath Sensor Based on Fiber-Tip Microcantilever.

Respiration rate is an essential vital sign that requires monitoring under various conditions, including in strong electromagnetic environments such as in magnetic resonance imaging systems. To provide an electromagnetically-immune breath-sensing system, we propose an all-fiber-optic wearable breath sensor based on a fiber-tip microcantilever. The microcantilever was fabricated on a fiber-tip by two-photon polymerization microfabrication based on femtosecond laser, so that a micro Fabry–Pérot (FP) interferometer was formed between the microcantilever and the end-face of the fiber. The cavity length of the micro FP interferometer was reduced as a result of the bending of the microcantilever induced by breath airflow. The signal of breath rate was rebuilt by detecting power variations of the FP interferometer reflected light and applying dynamic thresholds. The breath sensor achieved a high sensitivity of 0.8 nm/(m/s) by detecting the reflection spectrum upon applied flow velocities from 0.53 to 5.31 m/s. This sensor was also shown to have excellent thermal stability as its cross-sensitivity of airflow with respect to the temperature response was only 0.095 (m/s)/°C. When mounted inside a wearable surgical mask, the sensor demonstrated the capability to detect various breath patterns, including normal, fast, random, and deep breaths. We anticipate the proposed wearable breath sensor could be a useful and reliable tool for respiration rate monitoring.

A Wire-Free and Fiber-Based Smart T-Shirt for Real-Time Breathing Rate Monitoring

A new wearable smart T-Shirt design for breathing rate monitoring using Received Signal Strength Indicator (RSSI) is proposed. This new design features three principal functions: a wireless sensor to monitor the breathing rate, a wireless power transfer system, and a user interface to analyze the collected breathing data. First, the breathing curves obtained from a breathing sensor incorporated in a smart T-shirt were presented. Then, the data analysis methods are applied for extracting the important parameters for medical diagnosis. To observe multiple breathing profiles, additional results are presented for different tests on male and female subjects using another design of a smart T-shirt system consisting of an array of six sensors.

Highly sensitive breath sensor based on sonochemically synthesized cobalt-doped zinc oxide spherical beads

In this study, we introduce cobalt (Co)-doped zinc oxide (ZnO) spherical beads (SBs), synthesized using a sonochemical process, and their utilization for an acetone sensor that can be applied to an exhalation diagnostic device. The sonochemically synthezied Co-doped ZnO SBs were polycrystalline phases with sizes of several hundred nanometers formed by the aggregation of ZnO nanocrystals. As the Co doping concentration increased, the amount of substitutionally doped Co2+ in the ZnO nanocrystals increased, and we observed that the fraction of Co3+ in the Co-doped ZnO SBs increased while the fraction of oxygen vacancies decreased. At an optimal Co-doping concentration of 2 wt%, the sensor operating temperature decreased from 300 to 250 °C, response to 1 ppm acetone improved from 3.3 to 7.9, and minimum acetone detection concentration was measured at 43 ppb (response, 1.75). These enhancements are attributed to the catalytic role of Co3+ in acetone oxidation. Finally, a sensor fabricated using 2 wt% Co-doped ZnO SBs was installed in a commercially available exhalation diagnostic device to successfully measure the concentration of acetone in 1 ml of exhaled air from a healthy adult, returning a value of 0.44 ppm.

Breath Sensor Technology for the Use in Mechanical Lung Ventilation Equipment for Monitoring Critically Ill Patients.

Background: The need for mechanical lung ventilation is common in critically ill patients, either with COVID-19 infection or due to other causes. Monitoring of patients being ventilated is essential for timely and improved management. We here propose the use of a novel breath volatile organic compound sensor technology to be used in a mechanical lung ventilation machine for this purpose; the technology was evaluated in critically ill COVID-19 patients on mechanical lung ventilation. Methods: Based on the consistency results of our study data, the breath sensor device with metal oxide gas sensors and environment-controlling sensors was mounted on the ventilation exhaust port of the ventilation machine; this allowed to ensure additional safety since the device was placed outside the contour between the patient and equipment. Results: The sensors allowed stable registration of the signals for up to several weeks for 10 patients in total, depending on the storage amount; a proportion of patients were intubated or received tracheostoma during the evaluation period. Future studies are on the way to correlate sensor readings to other parameters characterizing the severity of the patient condition and outcome. Conclusions: We suppose that such technology will allow patient monitoring in real-time for timely identification of deterioration, potentially requiring some change of management. The obtained results are preliminary and further studies are needed to examine their clinical significance.

Calibration-free mid-infrared exhaled breath sensor based on BF-QEPAS for real-time ammonia measurements at ppb level

Breath analysis, compared with blood analysis, can enable real-time non-invasive diagnostics through quantification of exhaled biomarkers. Here, we demonstrate, for the first time, a calibration-free mid-infrared (MIR) exhaled breath sensor for real-time ammonia measurements at ppb-level, which can be used for the non-invasive diagnosis of liver and kidney diseases. The exhaled breath sensor employs a 10.359-μm MIR quantum cascade laser (QCL) to target a strong NH3 absorption line and adopts the beat-frequency quartz-enhanced photoacoustic technique (BF-QEPAS) to remove the requirements of calibration process and wavelength locking in the conventional QEPAS technique. By studying the adsorption-desorption effect and optimizing the modulation depth and modulation frequency of the sensor system, a detection limit of 9.5 ppb is achieved at an integration time of 3 ms. The ammonia content exhaled by 8 healthy volunteers is recorded and the real-time measurement results are analyzed. Compared with conventional QEPAS sensors, the proposed BF-QEPAS-based sensor offers higher sensitivity, faster response time, as well as no need for calibration and wavelength locking.

A review on chemi-resistive human exhaled breath biosensors for early diagnosis of disease

Human breath analysis provides a non-invasive and fast method for identifying numerous volatile organic compounds that are disease markers. Breath analysis on a small device that is connected to the Internet of Things and uses chemi-resistive semiconductor with extremely low energy usage will build new roads for detection of diseases and monitoring patients. Nano-structures of various forms, synthesized by diverse nano-meter-scale synthesis methods, can be utilized to achieve this aim. Metal oxide nano-structures allow a well-built gas-sensing layer interaction and, as a result, show a higher sensitivity than traditional materials due to features such as high surface-to-volume ratios and, consequentlya large number of surface sites exposed to gas. This paper provides an overview of advances in chemi-resistive nano-structures as gas sensing materials for exhaled breath detection, with the goal of assisting patients with various conditions in their disease screening. The many types of chemi-resistive materials utilized in breath sensors have been discussed, as well as their limits and future prospects also presented.

One-step synthesis of carbon-doped PPy nanoparticles interspersed in 3D porous melamine foam as a high-performance piezoresistive pressure, strain, and breath sensor

Flexible and compressible piezoresistive pressure, strain, and breath sensor based on carbon-doped PPy nanoparticles interspersed in 3D porous melamine foam.

A review on metal-oxide based trace ammonia sensor for detection of renal disease by exhaled breath analysis

Breath sensors have the potential to transform medical diagnostics by providing non-invasive and customised on-demand detection and monitoring of health indicators. The nanostructured film's gas sensing capacity is impressive in terms of response time, detection limit, & reversibility. In this work, we present advances in the detection of trace level ammonia vapor in breath, a bio-marker for renal disorders, using extremely selective, sensitive, and stable sensors at sub-ppm levels. This painless, efficient method will enhance the existing gold standard for detecting renal disease, allowing for speedy and early identification. At the end, we present an outlook for the upcoming development of efficient ammonia sensors.

Fiber-Optic Breathing Mask: An Alternative Solution for MRI Respiratory Triggering

This article provides the outcomes of complex testing of a novel low-cost and safe breathing sensor using fiber-optic technology under real magnetic resonance (MR) examination at 3 T. The sensor consists of the Bragg grating embedded into an oxygen breathing mask [i.e., fiber-optic breathing mask (FOBM)], thus minimizing movement artifacts and preventing MR interference. The obtained triggered MR images were evaluated using both objective and subjective image analysis methods, such as signal-to-noise ratio, contrast-noise ratio, and the analysis performed by radiologists. The system was compared with Siemens Prisma Respiratory Reference based on the navigator technique and pneumatic respiratory belt. Image quality assessment provided by radiologist experts shows that the FOBM approach provides reliable and accurate results since the overall image quality reached an average score of 3.3 ± 0.4, 3.7 ± 0.5, and 3.8 ± 0.2 for FOBM, Siemens respiratory reference, and respiratory belts, respectively.

Flexible Ni/NiOx-Based Sensor for Human Breath Detection.

We developed a simple methodology to fabricate an Ni/NiOx-based flexible breath sensor by a single-step laser digital patterning process of solution-processed NiOx thin-film deposited using NiOx nanoparticle ink. Laser-induced reductive sintering phenomenon enables for the generation of three parts of Ni electrodes and two narrow NiOx-sensing channels in between, defined on a single layer on a thin flexible polymer substrate. The Ni/NiOx-based breath sensor efficiently detects human breath at a relatively low operating temperature (50 °C) with fast response/recovery times (1.4 s/1.7 s) and excellent repeatability. The mechanism of the gas-sensing ability enhancement of the sensor was investigated by X-ray photoelectron spectroscopy analysis. Furthermore, by decoupling of the temperature effect from the breathing gas, the response of the sensor due to the temperature alone and due to the chemical components in the breathing gas could be separately evaluated. Finally, bending and cyclic bending tests (10,000 cycles) demonstrated the superior mechanical stability of the flexible breath sensor.

VOC Biomarker Monitoring for Diabetes Through Exhaled Breath Using Ag/P-TiO2 Composite Plasmonic Sensor

The detection of diabetes at an early stage is considered to be highly significant in the successful treatment of the disease. The patient has been reported to generate unique volatile organic compounds (VOCs) profiles in their exhaled breath which can be utilized as biomarkers to diagnosis the disease conditions. In this article, we theoretically report a simple breath sensor for the highly sensitive detection of isopropanol (IPA), which is the biomarker for both types of diabetes, in exhaled breath using a D-shaped composite plasmonic sensor (DSCPS). The sensing response of the sensor is characterized by using a full-vectorial finite element method (FEM) for the detailed analysis of DSCPS, where a porous TiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> (P-TiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) layer is used as low index sensing material on the top of thin Ag film. The design of the proposed sensor is based on the wavelength modulation technique. A maximum sensitivity of 0.25, 0.35, 0.45, and 1.35 nm/% can be achieved for 20%, 40%, 60%, and 80% volume fraction of IPA, respectively, with a 30% porosity of TiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , which is the maximum filled porous voids that provides the highest sensitivity.

Remarkably Stable Black Phosphorus Quantum Dots-Polyvinyl Alcohol Film as a Water Soluble Breath Sensor

This report demonstrates the fabrication and performance of a novel, transient, stable breath sensor based on black phosphorus quantum dots (BPQDs) and polyvinyl alcohol (PVA) composite. BPQDs were utilized as the conduction medium, while the PVA provides a flexible substrate that disintegrates in water. The device presents an innovative solution to black phosphorous (BP) degradation in which the copper (Cu) contacts are placed within the filler of the composite, ruling out the effects of surface degradation in the evaluation of the device performance. Stability studies at the end of eight weeks have been included wherein a negligible change in device performance to breath is observed. The sensor demonstrates chemiresistive properties with a change in resistance of ~100% to exhaled breath. The fabricated device was successful in identifying different breath patterns by monitoring the amplitude and the frequency of the device’s current change upon exposure to breath. The fabricated device achieves complete transience in ~10 min when immersed in water. The study opens up possibilities for applications in the fields of biosensors, military, and consumer electronics.

All solution processed flexible p-NiO/n-CdS rectifying junction: Applications towards broadband photodetector and human breath monitoring

Solution processable flexible devices meet the rising demand of sensors in wearable electronics owing to their cost-effective fabrication process with large area and throughput. This report demonstrates the multifunctional sensor based on p-NiO/n-CdS rectifying junction on ITO coated PET flexible substrate using low-temperature all solution processed deposition technique for UV–vis photodetection and breath monitoring applications. Under UV and visible light, the fabricated device exhibited strong current rectifying activity of approximately four orders. The responsivity (R) of the device underneath UV and visible illuminations found to be ~40.43 mAW−1 and ~25.96 mAW−1, respectively. Further, the device showed a response time of ~3.2 sec and detectivity of 1.4 × 1010 Jones under UV illumination. The internal electric field created at the p-NiO and n-CdS interface due to the formation of excellent rectifying junction assists in the efficient separation of photo-generated electron-hole pairs, thus improving the responsivity. Furthermore, the fabricated device was used as a breath sensor, and it was evaluated for different breath patterns of an individual. Interestingly, the device was able to distinguish between the different breath patterns (slow, fast, deep, etc.) The fabricated device displayed a negligible change in performance even after harsh deformations, indicating the flexibility and robustness of the device.

Selective Breath Sensors for Metabolic Monitoring

Introduction Despite a growing diagnostic toolset and a plethora of preventative and therapeutic interventions, a major challenge remains the control of epidemic diseases like obesity, diabetes or cancer. Great promise bears the current transformation of healthcare from disease-reactive to predictive, preventive, personalized and participatory - the so-called “4P” medicine [1]. Breath analysis could play a key role in this by providing on-demand critical health data. For daily breath analysis in wide-spread populations, simple-in-use and portable breath detectors are required. For this purpose, chemoresistive sensors are quite attractive due to their compact design, low cost and low power consumption being ideal for integration into handheld devices [2]. Here, I will describe recent progress on the development of selective/single-molecule breath sensors. In particular, I will showcase our recent in-vivo tests of Si-doped WO3 breath acetone sensors in a clinical environment during ketogenic dieting (KD) [3]. Finally, I will update on our newest development on orthogonal sensor arrays and present their application to sniff breath- and skin-emitted tracers (including acetone, isoprene and ammonia) for search & rescue applications [4]. Methods The sensor is based on a Si-doped WO3 nanoparticle films prepared by flame spray pyrolysis (FSP). Obtained nanoparticles were deposited directly by thermophoresis onto interdigitated Pt electrodes. End-tidal breath was extracted in a monitored and reproducible fashion with a tailor-made and modular sampler described in detail elsewhere [5]. The acetone sensor was mounted on a Macor holder, installed inside a Teflon chamber and fed with 130 mL min-1 from the sampler with a pump (SP 135 FZ, Schwarzer Precision). An additional line was connected just before the acetone sensor chamber to extract samples for the QMS (QMS 422, ThermoStarTM, Pfeiffer Vacuum). Healthy non-smokers free from respiratory or cardiovascular disease were included in this study. Each volunteer was informed about the experimental protocol prior to the test, gave written consent and could interrupt the test or withdraw consent anytime. The participants followed a fat:(carbohydrate+protein) 4:1 KD based on the Johns Hopkins protocol for 36 h including overnight fasting periods. Results and Conclusions Eleven volunteers (five female and six male) with a median age (± SD) of 22.7 (± 2.0) years participated in this study. Their body mass index was 22.4 (± 3.3) kg/m2. All volunteers had office jobs and were rather inactive. With the compact and inexpensive sensor, the individual breath acetone dynamics were monitored accurately up to concentrations of 66 ppm, in good agreement with mass spectrometry. The breath acetone dynamic reflected well the status of ketosis, as indicated by blood BOHB. Most interestingly, strong differences in individual breath and blood profiles were identified between the volunteers despite identical KD conditions. These were correctly recognized by the breath acetone sensor including patterns possibly associated to low tolerance to the KD protocol.As a result, this breath sensor is promising as a portable ketosis monitor. It has broad application as ketogenic diet is a proven medical treatment of refractory epilepsy (i.e. drug-resistant) [6] occurring in ~30% of the approx. 50 million epileptics worldwide. Also, it is an effective therapy for weight loss with growing interest to treat obesity-associated metabolic disorders [7] (e.g. diabetes or fatty liver disease), acts anti-inflammatory [8] and is even beneficial for athletes to improve their endurance performance by altering fuel preference [9].

Ultrasensitive Dual‐Mode Humidity Detection Using a Plasmonic‐Photonic Hybrid Waveguide

AbstractReliable and ultrasensitive humidity detection is essential in industrial process controls, meteorology, and medical diagnostics. In this study, a high‐performance relative humidity (RH) sensor driven by a plasmonic‐photonic hybrid system (PPHS), which supports waveguide modes and surface plasmon polariton mode simultaneously, is proposed. Due to the distinct sensitivities of these two modes to refractive index variation and volume expansion, the dual‐mode RH detection platform offers a unique tool for isolating the individual contribution of each effect and further revealing the mechanism of moisture absorption in a crosslinked PVA film. As an RH sensor, PPHS delivers a wavelength sensitivity of 1.16 nm %RH−1 (40–70 %RH) and an intensity sensitivity of 1.1 dB %RH−1 (55–90 %RH), respectively. Benefited from such an ultrahigh sensitivity, together with excellent recyclability and a quick response time of a few seconds, the PPHS shows an almost identical real‐time RH curve with an even higher resolution (&lt;0.1 %RH) compared to a commercial electrical hygrometer in the practical ambient RH monitoring. The PPHS is further demonstrated as a human breathing sensor and a skin‐humidity‐based noncontact switch, suggesting that the PPHS provides a great potential in medical diagnostics and optical modulation.

Detection and Classification of Human Activity for Emergency Response in Smart Factory Shop Floor

Factory shop floor workers are exposed to threats and accidents due to their encounters with tools, equipment, and toxic materials. There are cases of occupational accidents resulting in injuries to workers and precipitating lawsuits, which on the other hand affect company’s operational cost. To ensure the safety of workers within the shop floor, there is a need for proactive activity monitoring. Such activities include detection of falling objects, abnormal vibration, and movement of humans within an acceptable area of the factory floor. Breathing sensor-based monitoring of workers in the smart factory shop floor can also be implemented. This is for the detection of human activity, especially in cases where workers are in isolation with no available emergency assistance. Internet of Things (IoT), Industrial Internet of Things (IIoT), and machine learning (ML) have enabled so many possibilities in this area. In this study, we present a simple test-bed, which is made up of a vibration sensor, a breathing and movement sensor, and a Light Detection and Ranging (LIDAR) sensor. These sensors were used to gather normal and abnormal data of human activities at the factory. We developed a dataset based on possible real-life situations and it is made up of about 10,000 data points. The data was split with a ratio of 75:25 for training and testing the model. We investigated the performance of different ML algorithms, including support vector machine (SVM), linear regression, naive Bayes (NB), K-nearest neighbor (KNN), and convolutional neural network (CNN). From our experiments, the CNN model outperformed other algorithms with an accuracy of 99.45%, 99.78%,100%, and 100%, respectively, for vibration, movement, breathing, and distance. We have also successfully developed a dataset to assist the research community in this field.

Wavelength and intensity based lossy mode resonance breathing sensor

Copper oxide (CuO) allows the generation of lossy mode resonance (LMR) in a wide wavelength range of the optical spectrum, both in the visible and the near-infrared (NIR). For this, it is necessary to use a configuration based on the lateral incidence of light on the edge of a planar waveguide structure. On the other hand, the use of additional coatings of tin oxide (SnO2) and agarose allows an increase in the sensitivity of the sensor, in response to the breathing monitoring. The sensors were characterized, both in intensity and wavelength. In both cases their behavior depends on the position of the LMR in the optical spectrum. Therefore, it is convenient to extract the design rules that allow an optimal behavior of the sensor. In this sense, sensors located in the NIR presented a better behavior in terms of sensitivity and quality of the signal. In addition, the devices were tested in different conditions: repetitive tests at different distances, oral and nasal breathing, and breathing after doing physical exercise.

Highly selective, sensitive, and rapidly responding acetone sensor using ferroelectric ε-WO3 spheres doped with Nb for monitoring ketogenic diet efficiency

Abstract A ketogenic diet (KD) can enable more effective weight loss when performed with a portable breath acetone sensor capable of monitoring KD efficiency. However, current portable sensors—such as oxide semiconductor gas sensors—cannot selectively detect low concentrations of acetone in human breath, hindering their practical applications. Herein, we report an ultraselective and highly sensitive breath acetone sensor, established using WO₃ doped with 5–20 atom% Nb. The pure WO₃ sensor showed low gas responses (S = resistance ratio – 1) to all analytic gases, including acetone, ethanol, carbon monoxide, ammonia, hydrogen, and toluene (S = 0.1–2.1). In contrast, the 10 atom% Nb-doped WO₃ sensor exhibited a high gas response (S = 15.0 at 1 ppm) and ultrahigh selectivity to acetone over ethanol interference (response ratio = 22.3), even in highly humid conditions (relative humidity: 80 %). Moreover, the response time was as short as 4 s, and the detection limit was as low as 8.9 ppb, enabling breath acetone to be monitored in a rapid and precise fashion. The excellent acetone sensing performance of Nb-doped WO₃ sensors was then examined from diverse perspectives, including changes in porosity, surface area, oxygen adsorption, and charge-carrier concentration, and with respect to the formation of ferroelectric e-WO₃ domains caused by Nb doping. This work will trigger development of a new class of portable breath sensors that can be used to monitor KD efficiency.

Sensing gastric cancer via point‐of‐care sensor breath analyzer

Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant analysis (LDA) was used as a classifying model of the sensing signals obatined from the examined groups. For the testing step, an additional device was added. The study group included 274 patients: 94 with gastric cancer, 67 who were in the high-risk group, and 113 controls. The results of the test set showed a clear discrimination between patients with gastric cancer and controls using the 2-device LDA model (area under the curve, 93.8%; sensitivity, 100%; specificity, 87.5%; overall accuracy, 91.1%), and acceptable results were also achieved for patients with high-risk lesions (the corresponding values for dysplasia were 84.9%, 45.2%, 87.5%, and 65.9%, respectively). The test-phase analysis showed lower accuracies, though still clinically useful. Our results demonstrate that a portable breath sensor device could be useful in point-of-care settings. It shows a promise for detection of gastric cancer as well as for other types of disease. A portable sensor-based breath analyzer for detection of gastric cancer can be used in point-of-care settings. The results are transferrable between devices via advanced IoT technology. Both the hardware and software of the reported breath analyzer could be easily modified to enable detection and monitirng of other disease states.