Real-time Respiration Research Articles

Accessing Fungal Contributions to the Birch Effect: Real-Time Respiration from Pore-Scale Microfluidics

Drying and rewetting of soil stimulates soil carbon emission. The Birch effect, driven by these cycles, leads to CO2 efflux, which can be monitored using real-time mass spectrometry (RTMS). Although soil fungi retain water during droughts, their contribution to CO2 release during drying–rewetting cycles remains unclear. In this study, we present the first demonstration of integrating micromodels with RTMS to monitor the Birch effect by simulating drought and rewetting. Micromodels were inoculated with axenic fungal culture and dried to assess moisture retention. After drying, RTMS quantified CO2 release upon rewetting with H218O mixtures. Our results showed that soil fungi released CO2 upon rehydration and immediately utilized the external water source at the pore scale by generating subsequent 46CO2. This work is the first to integrate RTMS with microsystems to investigate pore-scale biogeochemistry and the involvement of fungi in the Birch effect.

All-printed MXene/WS2-based flexible humidity sensor for multi-scenario applications

As non-contact sensing, non-invasive medical diagnostics and environmental humidity monitoring technologies advance, the demand for high-performance humidity sensors is becoming increasingly apparent. Ti3C2Tx MXene is an attractive humidity-sensitive candidate due to its excellent chemical activity and hydrophilic surface. However, achieving fast responsiveness and high sensitivity of dynamic changes in humidity is still challenging. Herein, this work introduced a WS2-modified Ti3C2Tx MXene composite material as humidity sensing material with superior sensing performance. Then sodium carboxymethyl cellulose solution was added to the Ti3C2Tx MXene/WS2 composite material to adjust viscosity of the composite material, enabling the formulation of printable humidity-sensitive ink. Utilizing screen-printing technology, a mass-producible humidity sensor (CMXW2) was successfully fabricated. Experimental results show that the sensor has short response and recovery times of 4.65 s/1.33 s in the relative humidity of 11–97 % with a high humidity response of 1707 % and excellent mechanical properties. The efficacy of the humidity sensor for skin moisture monitoring, real-time respiration monitoring, and non-contact switch was also evaluated. The successful demonstration of multi-scenario applications using the CMXW2 humidity sensor opens up new possibilities and applications in the fields of smart healthcare and non-contact sensing.

Paper-based humidity sensor for wearable based on near-field electrohydrodynamic direct writing

Flexible humidity sensors have been widely used in wearable electronics, owing to their flexibility and compatibility with electronic device substrates. This study fabricated a flexible paper-based humidity sensor with a grid-like sensing film using the near-field electrohydrodynamic direct writing (NFEDW) method. A grid-like sensing layer with a dense network of carbon nanotubes/cellulose nanofiber (CNTs/CNF) was prepared, and induced by a voltage field applied during printing. The effects of the substrates and pattern width on the performance of the sensor were systematically investigated. The prepared sensor exhibited high sensitivity of 101 % at 95 % relative humidity (RH). An interlocking structure formed between the CNTs/CNF composite and the paper substrate, endowing the sensor with outstanding bending (minimum diameter of 5 mm) and folding (up to 100 times) durability. Furthermore, the prepared sensor exhibited rapid response performance (17 % within 10 s). This addresses the issue of long response time, which is typically associated with CNTs-based sensors, making these sensors more suitable to practical applications. The above-mentioned advantages enable the sensor to be used for respiration monitoring and even for vocal recognition. Finally, a real-time respiration monitoring platform was developed to demonstrate the sensor’s potential in wearable devices.

A high-performance humidity sensor based on 3D porous SnO2-encapsulated MCM-48 for real-time breath monitoring and contactless gesture detection

Ordered porous SnO2/MCM-48 was used as a basis for developing a resistive-type humidity sensor was demonstrated for real-time respiration monitoring and no-contact sensing for the first time.

In-fiber Mach-Zehnder interferometer for wearable respiration measurement

An in-fiber Mach-Zehnder interferometer based on single-mode fiberup-tapermultimode fiberup-tapersingle-mode fiber structure for respiration measurement is presented. The sensor probe is imbedded in a textile belt and fixed on the individual’s abdomen as a wearable solution. The system is used to detect the respiration rate of six volunteers, the respiration under different states is experimentally investigated. Attribute to the robust structural design and signal demodulation technique, the interference of temperature and body movement is reduced and the measurement accuracy and stability is distinctly improved. This simple, high accuracy, cost-effective wearable respiration sensor has great potential in real-time respiration monitoring.

Real-Time and Rapid Respiratory Response of the Soil Microbiome to Moisture Shifts.

Microbial response to changing environmental factors influences the fate of soil organic carbon, and drought has been shown to affect microbial metabolism and respiration. We hypothesized that the access of microbes to different carbon pools in response to dry-rewet events occurs sequentially at different rates. We amended desiccated soils with 13C-labeled glucose and measured the rates of 12CO2 and 13CO2 respiration in real time after rewetting. Using these differentiated 12CO2 and 13CO2 respiration rate soils after rewetting, we were able to deduce when microbes are accessing different pools of carbon. Immediately upon rewetting, respiration of 12CO2 occurred first, with negligible 13CO2 respiration. Appreciable metabolism and respiration of the added 13C glucose did not occur until 15 min after rewetting. We conclude that, while all carbon pools are being accessed in the first 9 h after rewetting, the rate and timing at which new and existing carbon pools are being accessed varies. Within this study, using stable isotope-labeled substrates to discern which carbon pools are metabolized first uniquely illustrates how microorganisms access different carbon pools which has implications into understanding how carbon metabolism can further affect climate, carbon sequestration, and soil health.

Iron Oxide-Based Nanoparticles for Fast-Response Humidity Sensing, Real-Time Respiration Monitoring, and Noncontact Sensing

Iron Oxide-Based Nanoparticles for Fast-Response Humidity Sensing, Real-Time Respiration Monitoring, and Noncontact Sensing

All-printed wearable humidity sensor with hydrophilic polyvinylpyrrolidone film for mobile respiration monitoring

In this study, a capacitive-type wearable humidity sensor comprising a polyvinylpyrrolidone (PVP) film, as active sensing dielectric, and carbon nanotube (CNT) random networks, as electrodes, all-printed on flexible substrates in ambient air, is demonstrated for real-time respiration monitoring. The PVP-based humidity sensor achieved a high sensing response of 3.0 ± 0.15 nF/RH%∙cm2 (where RH stands for relative humidity) and a sensitivity of 6.4 ± 0.1 pF/%RH in the RH range of 40–90%. A significantly small hysteresis window, fast response/recovery (∼ 30 ms), and high reliability were noted. The sensing mechanism of the capacitive response toward humidity was investigated, and it is attributed to continuous proton hopping through water molecule layers. The operational stability of the proposed humidity sensor under temperature variations and mechanical deformation, was investigated to address existing issues related to wearable electronics. Finally, the feasibility of a mobile respiration monitoring device is demonstrated by developing an armband-type wireless-communication monitoring system equipped with the wearable humidity sensor. Real-time biophysical information can be analyzed by monitoring the changes in the respiration intensity and frequency, which were wirelessly transmitted to the user’s mobile interface. We note that very few studies have focused on all-printed wearable humidity sensors consisting of pristine PVP and immobilized CNT random networks for real-time mobile respiration monitoring of human breath regardless of bent and relaxed state.

Ultrasonic-based submillimeter ranging system for contactless respiration monitoring

Wireless sensing technologies have exploited various methods for contactless respiration monitoring. One of the main methods is to use an acoustic beam to cover the chest and abdomen with real-time and high-resolution ranging. The system with high ranging resolution can detect small distance transformations, further affecting the precision of respiratory monitoring. However, the traditional range-based respiration monitoring systems are limited by an insufficient sampling rate and poor synchronization. The ranging resolution is between millimeters and centimeters. In this study, we introduced a novel, high-precision ultrasound-based system for contactless respiration monitoring. First, we developed a convenient and high-performance ultrasonic transceiver platform with universal serial bus audio architecture to eliminate the above limitations. The developed platform provides a foundation for acoustic sensing. Furthermore, based on this platform, we designed a cross correlation sine-frequency modulation continuous wave ranging method and a real-time respiration wave recovery method. The median error in monitoring respiration for 12 participants in three different sleep postures is 0 breaths/min, and the maximum error is 0.58 breaths/min. The proposed system has strong robustness concerning different respiration rates, long-term continuous respiration monitoring, and simulated apnea.

A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis.

Wireless sensing systems are required for continuous health monitoring and data collection. It allows for patient data collection in real time rather than through time-consuming and expensive hospital or lab visits. This technology employs wearable sensors, signal processing, and wireless data transfer to remotely monitor patients' health. The research offers a novel approach to providing primary diagnostics remotely with a digital health system for monitoring pulmonary health status using a multimodal wireless sensor device. The technology uses a compact wearable with new integration of acoustics and biopotentials sensors to monitor cardiovascular and respiratory activity to provide comprehensive and fast health status monitoring. Furthermore, the small wearable sensor size may stick to human skin and record heart and lung activities to monitor respiratory health. This paper proposes a sensor data fusion method of lung sounds and cardiograms for potential real-time respiration pattern diagnostics, including respiratory episodes like low tidal volume and coughing. With a p-value of 0.003 for sound signals and 0.004 for electrocardiogram (ECG), preliminary tests demonstrated that it was possible to detect shallow breathing and coughing at a meaningful level.

Wi-Breath: A WiFi-Based Contactless and Real-Time Respiration Monitoring Scheme for Remote Healthcare.

Respiration rate is an important healthcare indicator, and it has become a popular research topic in remote healthcare applications with Internet of Things. Existing respiration monitoring systems have limitations in terms of convenience, comfort, and privacy, etc. This paper presents a contactless and real-time respiration monitoring system, the so-called Wi-Breath, based on off-the-shelf WiFi devices. The system monitors respiration with both the amplitude and phase difference of the WiFi channel state information (CSI), which is sensitive to human body micro movement. The phase information of the CSI signal is considered and both the amplitude and phase difference are used. For better respiration detection accuracy, a signal selection method is proposed to select an appropriate signal from the amplitude and phase difference based on a support vector machine (SVM) algorithm. Experimental results demonstrate that the Wi-Breath achieves an accuracy of 91.2% for respiration detection, and has a 17.0% reduction in average error in comparison with state-of-the-art counterparts.

A Thermopile-Based Gas Flow Sensor with High Sensitivity for Noninvasive Respiration Monitoring.

In this work, a N/P polySi thermopile-based gas flow device is presented, in which a microheater distributed in a comb-shaped structure is embedded around hot junctions of thermocouples. The unique design of the thermopile and the microheater effectively enhances performance of the gas flow sensor leading to a high sensitivity (around 6.6 μV/(sccm)/mW, without amplification), fast response (around 35 ms), high accuracy (around 0.95%), and mood long-term stability. In addition, the sensor has the advantages of easy production and compact size. With such characteristics, the sensor is further used in real-time respiration monitoring. It allows detailed and convenient collection of respiration rhythm waveform with sufficient resolution. Information such as respiration periods and amplitudes can be further extracted to predict and alert of potential apnea and other abnormal status. It is expected that such a novel sensor could provide a new approach for respiration monitoring related noninvasive healthcare systems in the future.

A Real-Time Respiration Monitoring System Using WiFi Sensing Based on the Concentric Circle Model.

This paper proposes and experimentally validates a novel concentric circle (CC) model for indoor WiFi sensing. By setting the transmitter and receiver together, the perception model becomes concentric circles with equal spacing, eliminating the blind zone and unequal radial sensitivity problems of the Fresnel zone (FZ) model. Then a human respiratory monitoring system is developed based on this model, which executes the following steps: (1) Principal component analysis (PCA) is applied to the channel state information ratio (CSIR) as a preprocessing to extract the components related to human activities. (2) Human presence and respiratory signal detection are adopted to improve monitoring accuracy. (3) The Doppler respiratory frequency is extracted to calculate the respiratory rate. Experimental results show that the CC model achieves high accuracy in velocity measurement with an error of less than 0.4 cm/s. The respiration monitoring system can accurately monitor human respiration with an error of less than 0.7 bpm within 6 m.

In-House monitoring and measurement of respiration rateusing Disposable Paper Sensor

This present work provides an easily disposable paper-based interdigitated sensor embedded inside the mask for the detection of respiration rate continuously without direct contact with the human body. In present COVID scenario, everyone needs to wear mask for preventing the unwanted spreading of the said virus. But in tropical countries like India, People always complain about a suffocating situation while wearing mask. In order to address this, we have designed a non-invasive paper sensor that can be placed inside the mask (beneath nostril) for measuring breathing rate regularly to find out a cost-effective device capable of monitoring breathing rate. In general, we prefer use and throw type mask, thus the proposed paper-based sensor gives a cost-effective solution compared to the Current appliances of breathing sensing as most of them are burdensome, bulky, inconvenient as well as exorbitant than a paper-based respiration sensor. Essentially, these current approaches undergo through a practical limitation of frequency and time span i.e. static measurement. It is known that the humidity level of a paper changes according to the moisture content. Thus, it can easily detect the inhalation and exhalation through this changing. Moreover, variation of moisture level that happens due to breathing cycle changes the ionic conductivity of the sensor. The interdigitated design is the most suited for achieving higher sensitivity and easy to fabricate. First, we have designed it in Finite Element Method (FEM) based platform and finally this design is implemented with graphite-based electrodes on cellulose paper. Microcontroller based electronic circuitry is used in order to monitor and record the real-time respiration rate. It has been observed that the breathing rate as well as pattern gives a significant variation along with physical conditions and obstructive pulmonary diseases.

Multi-frequency Electrical Impedance Pneumography System as Point-Of-Care Device.

In this work we present the development of a multi-frequency electrical impedance pneumography (EIP) system based on a portable acquisition device and a mobile platform. This design is intended as an upgrade to our previous device for clinical use in the screening of patients with pulmonary diseases. The acquisition device uses the bioimpedance analog front end MAX30001, a mux/demux stage, Bluetooth 4.0 communication and an ESP32 microcontroller unit. It generates an excitation current of 8 μApp in a range of selectable frequencies from 1 kHz to 130 kHz. The mobile platform provides a real-time respiration signal at 64 S/s and allows the configuration of the device. Results show less error in higher frequencies, which are the most common in these applications, ensuring the feasibility of the system for use in humans. Some hardware constraints related to EIP integrated circuits are discussed, an their effect in the signal acquisition.

Carbon nanodot-based humidity sensor for self-powered respiratory monitoring

Developing low-cost, portable, and high-performance humidity sensors for respiratory monitoring has received considerable attention in recent years. Herein, humidity sensors have been fabricated based on carbon nanodots (CDs), which exhibit high sensitivity (5318%) at 94% relative humidity (RH) and excellent long-time stability under the RH range of 11% to 94%. The high sensitivity can be attributed to the adsorption of the water molecules by the massive hydrophilic functional groups on the surface of CDs. By introducing a breath-driven triboelectric nanogenerator (TENG), the self-powered humidity sensor is developed for the first time, exhibiting a wide sensing range (11–94% RH) and excellent stability. The maximum output voltage of the TENG is up to 200 V and the maximum short-circuit current is about 9.2 μA. Furthermore, the self-powered humidity sensor further demonstrates the potential ability for real-time respiration monitoring, which can detect different breathing statuses. This work provides a convenient and low-cost strategy for constructing sensitive CDs-based humidity sensors, and prospects their applications in respiratory monitoring systems.

Simulating the IMA Recipient Site for DIEP Flap Surgery: A New Model for Dynamic Microsurgery Simulation with Real-Time Respiration and a Pilot Study.

Breast reconstruction (BR) using autologous free flaps has been shown to have numerous psychosocial and quality-of-life benefits. Unfortunately, the microsurgical learning curve is quite steep due to some unique operative challenges. Currently, there is no realistic simulation model that captures real-life respiratory excursion and the depth of internal mammary vessels within the compact recipient site. The purpose of this study was to delineate intraoperative measurements of depth and motion, describe the resulting simulation model, and conduct a pilot study evaluating the simulator as an educational resource. This is a single-center, ethics-approved study. For the intraoperative measurements, all consecutive patients undergoing free flap BR using internal mammary vessels as recipients were recruited. Patient and intraoperative factors as well as intraoperative measurements were recorded. A dynamic model was developed based on intraoperative parameters. For the pilot study, plastic and reconstructive surgery trainees were recruited to complete a hand-sewn internal mammary artery (IMA) anastomosis using the new simulator and completed objective questionnaires pre- and postsimulation. Subjective feedback was recorded and themes determined. Fifteen operative sites were analyzed. Flap pocket was found to be between 4 and 5 cm in depth with vertical excursion of 3.7 ± 1.0mm and a respiratory rate of 9 to 14 breaths/minute. Previous radiation, rib space, body mass index (BMI), blood pressure, heart rate, tidal volume, and respiratory rate showed no correlation to vessel depth/excursion. Laterality, rib space, BMI, radiation, vitals, and tidal volume had no correlation with vessel movement. Twenty-two trainees were included in the pilot. An increase in confidence and mixed results for anxiety was reported. This study reports a novel microsurgical simulation model that provides a realistic deep inferior epigastric perforator free flap BR IMA anastomosis experience. It replicates movement of vessels in situ with real-time respiratory excursion and similar physical structures of the internal mammary system. This model shows promising results for increased use in microsurgical education.

MXene/MWCNT electronic fabric with enhanced mechanical robustness on humidity sensing for real-time respiration monitoring

Humidity sensing-based wearable respiration monitoring systems have promising application prospects in providing the critical health information. Currently, due to the inherent flexibility and compatibility, fabric-based wearables have attracted tremendous interest in humidity sensing. Herein, we proposed a humidity sensor made from fabric coated with MXene and multi-walled carbon nanotubes (MWCNT). The sensor showed 265% response at 90% relative humidity (RH) and great response stability under deformation. The humidity response of MXene/MWCNT fabric (MC-fabric) sensor only varied 7% under stretch, which is greatly alleviated compared with pristine MXene fabric sensor (35% under stretch). The MC-fabric sensor, integrated into a mask, can accurately identify diverse human respiration patterns despite the deformation caused by motions. This work not only offers a facile modification strategy to enhance the sensing robustness under deformation, but also provides a feasible method for real-time breath analysis.

A Real-Time Respiration Monitoring and Classification System Using a Depth Camera and Radars.

Respiration rate (RR) and respiration patterns (RP) are considered early indicators of physiological conditions and cardiorespiratory diseases. In this study, we addressed the problem of contactless estimation of RR and classification of RP of one person or two persons in a confined space under realistic conditions. We used three impulse radio ultrawideband (IR-UWB) radars and a 3D depth camera (Kinect) to avoid any blind spot in the room and to ensure that at least one of the radars covers the monitored subjects. This article proposes a subject localization and radar selection algorithm using a Kinect camera to allow the measurement of the respiration of multiple people placed at random locations. Several different experiments were conducted to verify the algorithms proposed in this work. The mean absolute error (MAE) between the estimated RR and reference RR of one-subject and two-subjects RR estimation are 0.61±0.53 breaths/min and 0.68±0.24 breaths/min, respectively. A respiratory pattern classification algorithm combining feature-based random forest classifier and pattern discrimination algorithm was developed to classify different respiration patterns including eupnea, Cheyne-Stokes respiration, Kussmaul respiration and apnea. The overall classification accuracy of 90% was achieved on a test dataset. Finally, a real-time system showing RR and RP classification on a graphical user interface (GUI) was implemented for monitoring two subjects.

Assessing Changes in Human Natural Killer Cell Metabolism Using the Seahorse Extracellular Flux Analyzer.

Natural killer (NK) cells are cytotoxic cells that mediate anti-tumor and anti-viral immunity. The response of NK cells to different cytokines and stimuli may involve cell survival, proliferation, and changes in their cytotoxic function. These responses will be supported by changes in cellular metabolism. Therefore, changes in NK metabolic parameters could somehow predict changes in NK cell function and cytotoxicity. In this chapter, we describe a protocol to measure NK cell metabolism in primary human NK cells by using an extracellular flux analyzer. This machine measures pH and oxygen changes in the medium and allows the study of NK cell glycolysis and mitochondrial respiration in real time with a small number of cells.