Real-time Respiratory Monitoring Research Articles

Lead free halide perovskite embedded PVDF based efficient mechanical energy harvester: Self-driven respiratory sensor

Lead-free inorganic perovskites have emerged as a promising material for energy harvesting applications, owing to their superior optoelectronic properties. This enables the insertion of lead-free halide perovskites into polyvinylidene difluoride (PVDF) to feasibly enhance its piezoelectric coefficient. Consequently, piezoelectric nanogenerators based on PVDF composite have evolved as a futuristic, sustainable, and renewable energy alternative due to their flexible, durable, and nontoxic behavior. Herein, we realized a novel composite by incorporating different mass-fractions of pre-synthesized CsCuCl3 particles in the polymer matrix. Notably, the composite containing 4 wt% CsCuCl3 perovskite nucleates an optimum electroactive phase fraction of about ∼93 %. A first-principles investigation is also carried out in order to fully comprehend the interfacial interaction of the PVDF dipole with the CsCuCl3 system. Thereafter, the piezo-sensors are fabricated utilizing the composites, where the 4 wt% CsCuCl3/PVDF- based device delivered optimal output performance owing to its highest electroactive phase. This optimized device, viz., PNG 4 achieves an open-circuit voltage and short-circuit current of ∼73.2 V and ∼5.44 μA, respectively. Besides, the optimized device could operate as a piezo-resistive sensor as well as a pressure sensor. An excellent sensing performance was achieved from the PNG 4 device, where the sensing parameter (∆II0) reached values as high as ∼98.7. The optimized device is efficient in the low-pressure region and exhibits a high sensitivity of 13.8 kPa−1 with notable response ≤26ms and recovery time≤75ms. Furthermore, the device is capable of sensing different bending states with a sensitivity of 0.5/degree, which proves its potential for applications in human health care monitoring regarding self-powered real-time respiratory monitoring systems.

A versatile nanofibrous facemask filter for triboelectric nanogenerator-based self-powered respiratory monitoring with efficient filtration and excellent antibacterial capacities

Respiration, as a basic human physiological process, can be used as a vital indicator for early disease diagnosis. Moreover, the prevention of respiratory diseases caused by particulate matter and bacteria is of great importance. Herein, a smart face mask with self-powered real-time respiratory monitoring, efficient filtration and excellent antibacterial activity was fabricated by electrospinning. By applying polyvinylidene fluoride (PVDF)/ε-poly (L-lysine)(ε-PL) and poly (ε-caprolactone)(PCL)/gelatin nanofibrous membranes as contact electrification pairs, the triboelectric nanogenerator assembled into a face mask could detect different breathing frequencies and intensities without external power supply. The electrical output performance was increased with the increment of PVDF concentration and the introduction of gelatin. Efficient filtration of particulate matter was achieved under a low pressure drop. Furthermore, PVDF/ε-PL nanofibrous membrane also exhibited excellent antibacterial activity, thus reducing the risk of respiratory infection. The prepared smart face mask is hopeful for personal healthcare management and prevention of respiratory diseases.

SnO2 nanostructured thin film as humidity sensor and its application in breath monitoring

In the present paper, we studied SnO2 nanostructured thin film-based resistive type humidity sensor fabricated by spin coating method on alumina substrate and showed its application in real time respiratory monitoring. Experiments show the growth of crystalline SnO2 nanoparticles with a tetragonal phase, with an average particle size of ∼15 nm and a high surface roughness of the order of 50-60 nm. The gold-interdigitated electrodes were patterned on the SnO2 film surface by DC sputtering technique to study the sensing response of the film. The sensor shows a high sensitivity of 1.34 kΩ/%RH, a minimal hysteresis of 0.94%, and good repeatability. The developed sensor is tested for monitoring human breath patterns in different physical conditions, and apnea like situations, which suggests its potential for clinical applications. Overall, the present work proposes an environmental friendly, easy-to-synthesize, highly stable, and simple facile SnO2 based deployable humidity sensor to diagnose human health patterns in a non-contact manner.

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.

MXene effectively enhances the electron-withdrawing (EW) ability and dielectric properties of PVDF-TrFE nanofibers for triboelectric nanogenerators

Functional fillers can improve the triboelectric characteristics of polyvinylidene difluoride (PVDF)-based material, a typical triboelectric nanogenerator (TENG) negative dielectric layer material. MXene fillers can significantly enhance the triboelectric characteristics of PVDF-based negative dielectric layers by dielectric modulation. However, the effect of MXene as a highly electronegative filler on the electron-withdrawing (EW) ability of PVDF/MXene composite films is frequently ignored. In this work, polyvinylidene fluoride-trifluoro-ethylene (PVDF-TrFE)/MXene (Ti3C2Tx) composite nanofibers films (PMNFs) are prepared by electrospinning. When the MXene content is 0.8 wt%, PMNFs-based TENG achieves a maximum output power density of 250 mW/m2 at a matching external load resistance of 4 MΩ and a maximum open-circuit voltage (VOC) of 85 V, 2.66 times higher than that of the PVDF-TrFE-based TENG. Enhancing the EW ability and the dielectric properties by adding MXene are considered and proven by examining the work function (WF) and dielectric constant (and loss), respectively. Finally, we design a tremor-based TENG by PMNFs and develope a novel respiratory monitor to achieve real-time respiratory monitoring, which should offer fresh perspectives on creating respiratory monitoring devices.

Multi-modal piezoresistive sensor based on cotton fiber aerogel/PPy for sound detection and respiratory monitoring

At present, most wearable flexible sensors can satisfy the requirements of sensitivity and wide response range. However, how to prepare sensors with good sensing performance and integration functions is still an urgent problem to be solved. Herein, the multimodel piezoresistive sensor integrating sound recognition, airflow detection and respiration monitoring was manufactured by vapor deposition of polypyrrole on cotton fiber aerogel (CA@PPy). The sensor exhibits wide response range (0–122.50 kPa), high stability (over 4500 cycles), high pressure resolution (0.2%) and ultra-light density (27.5 mg/cm3). Besides detecting normal human motion signals, it can also capture biological/abiotic sound signals with excellent sensitivity (minimum detection limit is 56 dB). Moreover, the sensor can also be used to detect the air flow rate with the minimum flow rate of 0.09 m/s, providing real-time respiratory monitoring for patients with respiratory diseases. We believe that this integrated multimode sensor will have great application potential in flexible electronics and bring great convenience to people's lives.

Electrothermal sterilization and self-powered real-time respiratory monitoring of reusable mask based on Ag micro-mesh films

Since the COVID-19 pandemic outbreaks, the utilization of medical masks plays a critical role in reducing the infected risk. However, constructing multifunctional masks to achieve simultaneously self-sterilization, reusability, and respiratory monitoring capability remains still a huge challenge. Herein, a reusable Ag micro-mesh film-based mask is proposed, which enables the capabilities of electrothermal sterilization and self-powered real-time respiratory monitoring. Highly conductive Ag micro-mesh films prepared by continuous draw spinning method demonstrate excellent electrothermal performances for thermal sterilization and serve as working electrode to fabricate triboelectric nanogenerator (TENG) for real-time respiratory monitoring, respectively. Under a low driving voltage of 3.0 V, the surface temperature of Ag micro-mesh film enables a quick increase to over 60 °C within 30 s, which endows thermal sterilization against S. aureus with antibacterial efficiency of 95.58 % within 20 min to achieve the self-sterilization of medical masks. Furthermore, a self-powered alarm system based on the fabricated TENG as respiratory monitor is developed for real-time respiratory monitoring to render a timely treatment for patients in danger of tachypnea and apnea. Consequently, this work has paved a new and practical avenue to achieve reusable multifunctional masks with capabilities of electrothermal sterilization and real-time respiratory monitoring in clinical medicine.

Air-permeable cellulosic triboelectric materials for self-powered healthcare products

Wearable electronics with high-efficiency particulate matters (PMs) filtration and real-time respiratory monitoring offer everyone the opportunity to own a personal healthcare system. However, the power supply, breathability, and filtration performance of wearable electronics still have many challenges that need to be overcome. Herein, a self-powered air filter based on a respiration-driven triboelectric nanogenerator (R-TENG) was integrated with facemask for efficiently filtering submicron particles and respiration monitoring. The conductive cellulose aerogel/MOF composite, regarded as filtration and triboelectric material, was designed by in-situ and green synthesis method. The R-TENG was fabricated using conductive cellulose aerogel/MOF composite and polyvinylidene fluoride (PVDF) film as positive and negative triboelectric materials, respectively. Enabled by its desirable porous network structure and unique electricity generation feature, the air filter is capable of removing PM1.0 and PM0.5 and PM0.3 with high efficiency of 98.4 %, 97.3 % and 95.0 %, while maintaining a relatively low pressure drop of 86 Pa. Moreover, the air filter system can monitor breathing status without using an external power supply for disease prevention and medical diagnosis. This work designs a self-powered mask filter based on conductive cellulose aerogel/MOF composite with both PMs filtration and respiratory monitoring capabilities, which has excellent potential for air purification and healthcare applications.

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.

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.

Helical Fiber Strain Sensors Based on Triboelectric Nanogenerators for Self-Powered Human Respiratory Monitoring.

Respiration is a major vital sign, which can be used for early illness diagnosis and physiological monitoring. Wearable respiratory sensors present an exciting opportunity to monitor human respiratory behaviors in a real-time, noninvasive, and comfortable way. Among them, fiber-shaped triboelectric nanogenerators (FS-TENGs) are attractive for their comfort and high degree of freedom. However, the single-electrode FS-TENGs cannot respond to their own tensile strains, and the coaxial double-electrode FS-TENGs show low sensitivity to strain due to structural limitations. Here, a type of helical fiber strain sensor (HFSS) is developed, which can respond to tiny tensile strains. In addition, a smart wearable real-time respiratory monitoring system is developed based on the HFSSs, which can measure some key breathing parameters for disease prevention and medical diagnosis. An intelligent alarm can automatically call a preset mobile phone for help in response to respiratory behavior changes. This work provides an effective helical structure for fabricating highly sensitive strain sensors based on FS-TENGs and develops wearable self-powered real-time respiratory monitoring systems.

Reusable Multifunctional Mask Based on Ag Micro-Mesh Films for Electrothermal Sterilization and Self-Powered Real-Time Respiratory Monitoring

Reusable Multifunctional Mask Based on Ag Micro-Mesh Films for Electrothermal Sterilization and Self-Powered Real-Time Respiratory Monitoring

A Wearable Bioimpedance Chest Patch for IoHT-Connected Respiration Monitoring.

This paper presents a wearable sensor patch with real-time respiration monitoring by measuring the change in thoracic impedance resulting from breathing. A bioimpedance (BioZ) sensor with two sensing electrodes is employed to measure the chest impedance. In addition, a medical-grade infrared temperature sensor is utilized to detect body temperature. The recorded data is transmitted via a Bluetooth module to a computer for online data computation and waveform visualization. The breath-by-breath breathing rate is calculated using the time difference between two BioZ signal peaks, and the results are validated against a commercial respiration monitoring belt. Experimental tests have been conducted on five subjects in both static (i.e., sitting, supine, sleeping on the left side, sleeping on the right side, and standing) and dynamic (i.e., walking) conditions. The experiment measurements show that the BioZ sensor patch can be used to monitor the breathing rate accurately in static conditions with a low mean absolute error (MAE) of 0.71 breath-per-minute (bpm) and can detect breathing rate effectively in a dynamic environment as well. The results suggest the feasibility of using the proposed approach for respiration monitoring in daily life.

High-Mechanical-Resolution Pressure Sensor Based on Melt-Blown Fibers in Integrated Wearable Mask for Respiratory Monitoring

With the worldwide spreading of the dreaded COVID-19 epidemic, wearing masks becomes the most effective approach to prevent infectious respiratory diseases from transmission, for continuous monitoring of respiratory signals acts as a significant status in the treatment of respiratory diseases. Herein, a convenient mask-based respiration sensor was designed to access multiple high-resolution respire-related states in a wearable and noninvasive manner. Combining the intrinsically low compression strains and large contact domains of the melt-blown fibers with continuously optimized multi-purpose (improve electrical property, regulate mechanical modulus, and enhance environmental stability) conductive materials together, the fabricated sensor exhibited a high sensitivity of 43.6 per kilopascal, a rapid response time of 28 ms as well as low fatigue over 10,000 s. Furthermore, a wearable mask that integrated respiration sensor is capable of collecting a variety of breathing states, including cough, exercise, sit, and other multiple patterns correlated respiratory dynamics. As a result, it can provide a facile and low-overhead designing strategy for human respiratory analysis, which enables real-time respiratory monitoring with this wearable device to protect against respire-related diseases.

Ion Gel Coated Graphene Field Effect Transistor for Humidity Sensing Applications

Humidity sensors are crucial for weather forecasting, instrumentation and industrial processes, agriculture and real-time respiratory monitoring. Nevertheless, the sensitivity and response time are the key parameters, particularly, for the clinical applications. Here, we demonstrate an ion gel coated graphene field effect transistor (GFET) for humidity sensing. The ion gel, in addition to being a gate dielectric, acts also as a humidity sensing layer. Indeed, water molecules from the surrounding attach onto the surface of the ion gel due to the presence of the hydrophilic poly(ethylene glycol) diacrylate (PEGDA) monomer in it. The water molecules, being polar, act as a gate bias thereby modulating the current transport in the GFET. The sensor's sensitivity, in terms of the normalized current change per percent relative humidity (RH), is 0.0014 in the low sensitivity regime (<; 71% RH) and 0.0135 in the high sensitivity regime (>71% RH). The sensor swiftly detects the human respiration with a response time of 350 ms. Moreover, a stable response over an extended period of four weeks demonstrates the sensor's stability.

Synthesis of high response gold/titanium dioxide humidity sensor and its application in human respiration

A high response humidity sensor based on Au nanoparticles (AuNPs) modified TiO2 (Au/TiO2) was designed for real-time monitoring of human respiration. Effects of Ti3+ defect content on the performance of TiO2 humidity sensor was further explored. Experiments show that AuNPs can make more Ti3+ defects to appear on TiO2 surface to enhance hydrophilicity of the materials, which can greatly enhance response of the humidity sensor. AuNPs can also increase oxygen vacancy and hydroxyl content on the surface of TiO2 to promote decomposition of water molecules into conductive ions and to accelerate the process of proton conduction. Such an Au/TiO2 humidity sensor shows high response (84366.9), good linearity, low hysteresis (4.76%) and high reliability in the range of RH from 11% to 95%. In addition, Au/TiO2 humidity sensor can effectively detect different breathing states and skin surface moisture, showing strong application potential in real-time respiratory monitoring and non-contact sensing. This research has further enriched factors that affect the performance of TiO2 humidity sensors, and also provides a possibility for the development of high-performance TiO2 respiration sensors.

Surface imaging for real-time patient respiratory function assessment in intensive care.

Monitoring of physiological parameters is a major concern in Intensive Care Units (ICU) given their role in the assessment of vital organ function. Within this context, one issue is the lack of efficient noncontact techniques for respiratory monitoring. In this paper, we present a novel noncontact solution for real-time respiratory monitoring and function assessment of ICU patients. The proposed system uses a Time-of-Flight depth sensor to analyze the patient's chest wall morphological changes in order to estimate multiple respiratory function parameters. The automatic detection of the patient's torso is also proposed using a deep neural network model trained on the COCO dataset. The evaluation of the proposed system was performed on a mannequin and on 16 mechanically ventilated patients (a total of 216 recordings) admitted in the ICU of the Brest University Hospital. The estimation of respiratory parameters (respiratory rate and tidal volume) showed high correlation with the reference method (r=0.99; P<0.001 and r=0.99; P<0.001) in the mannequin recordings and (r=0.95, P<0.001 and r=0.90, P<0.001) for patients. This study describes and evaluates a novel noncontact monitoring system suitable for continuous monitoring of key respiratory parameters for disease assessment of critically ill patients.