Real-time Respiratory Monitoring Research Articles

Water Molecule-Triggered Anisotropic Deformation of Carbon Nitride Nanoribbons Enabling Contactless Respiratory Inspection

The exploitation of the interaction between nanostructured matter and small molecules, such as H2O at interfaces via dynamic hydrogen bonding, is essentially the key for smart, responsive nanodevic...

Cu(OH)2 nanowires/graphene oxide composites based QCM humidity sensor with fast-response for real-time respiration monitoring

Respiration is an essential physiological process of human body and acts as a vital sign for personal health. Humidity sensing is a promising way to monitor respiration based on the humidity change when people breathing. Here we demonstrate Cu(OH)2 nanowires and graphene oxide (GO) based quartz crystal microbalance (QCM) humidity sensor for real-time respiration monitoring. The Cu(OH)2 nanowires/GO composites humidity-sensitive film was fabricated by the method of in-situ growth and drop-casting. The morphology and structure of the Cu(OH)2 nanowires/GO composites were characterized by energy dispersive spectrometer (EDS), Raman, Fourier transform infrared (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopic (TEM), high resolution TEM (HRTEM), and energy dispersive X-ray spectroscopy (EDXS). The nanocomposites with large surface area and abundant oxygen-rich functional groups lead to good humidity sensing performance. When changing relative humidity (RH) between 0 and 80%, our device exhibits high sensitivity (52.1 Hz/%RH), fast response and recovery (within 1.9 s and 7.6 s, respectively) and high linearity (R2 = 0.9968). Different breathing patterns can be distinguished, including normal breathing, apnea, speaking, nose and mouth respiration, and humidity variations before and after water intake, showing potential applications in analyzing human health-status.

An Active Self-Driven Piezoelectric Sensor Enabling Real-Time Respiration Monitoring.

In this work, we report an active respiration monitoring sensor based on a piezoelectric-transducer-gated thin-film transistor (PTGTFT) aiming to measure respiration-induced dynamic force in real time with high sensitivity and robustness. It differs from passive piezoelectric sensors in that the piezoelectric transducer signal is rectified and amplified by the PTGTFT. Thus, a detailed and easy-to-analyze respiration rhythm waveform can be collected with a sufficient time resolution. The respiration rate, three phases of respiration cycle, as well as phase patterns can be further extracted for prognosis and caution of potential apnea and other respiratory abnormalities, making the PTGTFT a great promise for application in long-term real-time respiration monitoring.

Contactless Respiration Monitoring Using Ultrasound Signal With Off-the-Shelf Audio Devices

Recent years have witnessed advances of Internet of Things technologies and their applications to enable contactless sensing and elderly care in smart homes. Continuous and real-time respiration monitoring is one of the important applications to promote assistive living for elders during sleep and attracted wide attention in both academia and industry. Most of the existing respiration monitoring systems require expensive and specialized devices to sense chest displacement. However, chest displacement is not a direct indicator of breathing and thus false detection may often occur. In this paper, we design and implement a real-time and contactless respiration monitoring system by directly sensing the exhaled airflow from breathing using ultrasound signals with off-the-shelf speaker and microphone. Exhaled airflow from breathing can be regarded as air turbulence, which scatters the sound wave and results in Doppler effect. Our system works as an acoustic radar which transmits sound wave and detects the Doppler effect caused by breathing airflow. We mathematically model the relationship between the Doppler frequency change and the direction of breathing airflow. Based on this model, we design a minimum description length-based algorithm to effectively capture the Doppler effect caused by exhaled airflow. We conduct extensive experiments with 25 participants (7 elders, 2 young kids, and 16 adults, including 11 females and 14 males) in four different rooms. The participants take four different sleep postures (lying on one’s back, on right/left side, and on one’s stomach) in different positions of the bed. Experiment results show that our system achieves a median error lower than 0.3 breaths/min (2%) for respiration monitoring and can accurately identify Apnea. The results also demonstrate that the system is robust to different respiration styles (shallow, normal, and deep), respiration rate variation, ambient noise, sensing distance variation (within 0.7 m), and transmitted signal frequency variation.

Air-Flow-Driven Triboelectric Nanogenerators for Self-Powered Real-Time Respiratory Monitoring.

Respiration is one of the most important vital signs of humans, and respiratory monitoring plays an important role in physical health management. A low-cost and convenient real-time respiratory monitoring system is extremely desirable. In this work, we demonstrated an air-flow-driven triboelectric nanogenerator (TENG) for self-powered real-time respiratory monitoring by converting mechanical energy of human respiration into electric output signals. The operation of the TENG was based on the air-flow-driven vibration of a flexible nanostructured polytetrafluoroethylene (n-PTFE) thin film in an acrylic tube. This TENG can generate distinct real-time electric signals when exposed to the air flow from different breath behaviors. It was also found that the accumulative charge transferred in breath sensing corresponds well to the total volume of air exchanged during the respiration process. Based on this TENG device, an intelligent wireless respiratory monitoring and alert system was further developed, which used the TENG signal to directly trigger a wireless alarm or dial a cell phone to provide timely alerts in response to breath behavior changes. This research offers a promising solution for developing self-powered real-time respiratory monitoring devices.

Development of a hydrogen cyanide inhalation exposure system and determination of the inhaled median lethal dose in the swine model

Objective: Cyanide is a highly toxic chemical, and acute exposure depletes cells and tissue of oxygen, depressing the respiratory, cardiovascular and neurological systems and potentially leading to death. Cyanide has been used as a weapon since ancient Rome and continues to pose a potential threat today. A well-characterized animal model is necessary for the development of novel methods of rapid detection and treatment. This manuscript describes the development of an inhalation exposure system designed to evaluate the lethality of acute cyanide inhalation in the porcine model.Materials and Methods: A custom designed hydrogen cyanide (HCN) inhalation exposure system provided stable cyanide concentrations to un-anesthetized swine while monitoring respiratory parameters. Real-time respiratory monitoring, cyanide concentration and body weight were used to calculate inhaled doses.Results: The inhalation exposure system generated controlled HCN ranging from 260 to 986 ppm to achieve inhaled doses between 1.78 and 3.97 mg/kg. Based on survival outcomes, the median lethal dose was determined to be 2.21 mg/kg, and the median lethal exposure level was 5893 mg min/m3.Discussion: The ability of the HCN inhalation exposure system to deliver target inhaled doses and the determination of the inhaled median lethal dose in swine support the use of the exposure system and animal model for the evaluation of medical countermeasures of acute inhaled HCN toxicity.

Amygdala-stimulation-induced apnea is attention and nasal-breathing dependent.

Evidence suggests that disordered breathing is critically involved in Sudden Unexpected Death in Epilepsy (SUDEP). To that end, evaluating structures that are activated by seizures and can activate brain regions that produce cardiorespiratory changes can further our understanding of the pathophysiology of SUDEP. Past preclinical studies have shown that electrical stimulation of the human amygdala induces apnea, suggesting a role for the amygdala in controlling respiration. In this study, we aimed to both confirm these findings in a larger group of patients with intractable temporal lobe epilepsy (TLE) and also further explore the anatomical and cognitive properties of this effect. Seven surgical TLE patients had depth electrodes implanted in the amygdala that were used to deliver electrical stimulation during functional mapping preceding resection. Real-time respiratory monitoring was performed in each patient to confirm apnea. Our data confirm that amygdala stimulation reliably induces apnea (occurring in all 7 patients) and further suggest that apnea can be overcome by instructing the patient to inhale, and can be prevented entirely by breathing through the mouth before electrical stimulation. Finally, stimulation-induced apnea occurred only when stimulating the medial-most amygdalar contacts located in the central nucleus. These findings confirm a functional connection between the amygdala and respiratory control in humans. Moreover, they suggest specific amygdalar nuclei may be critical in mediating this effect and that attentional state is critical to apnea mediated by amygdala activation-perhaps alluding to future development of strategies for the prevention of SUDEP. Ann Neurol 2018;83:460-471.

Refinement of invivo optical imaging: Development of a real-time respiration monitoring system.

Invivo optical imaging enables detection and quantification of light-emitting compounds from the whole body in small animals such as the mouse, but it typically requires the use of anaesthetics for subject immobilisation due to long exposure times. Excessively deep anaesthesia can result in unacceptably compromised physiology, whilst excessively light anaesthesia can result in animals waking up. Here we report a respiratory monitoring setup for an invivo bioluminescence and fluorescence imaging device which simultaneously allows real-time adaptive control of anaesthesia depth in multiple animals to (i) potentially increase the consistency between animals, (ii) ensure animals are maintained within minimally intrusive, adequate anaesthetic plane and (iii) provide a valuable refinement strategy for a common challenge within animal-based research.

A new contactless magneto-LC resonance technology for real-time respiratory motion monitoring

Monitoring the rate of respiration and its pattern is crucial to assessing an individual’s health or progression of an illness, creating a pressing need for fast, reliable and cost-effective monitors. We present here a novel respiratory monitoring technology based on a magnetic microwire coil (MMC) magneto-LC resonance sensor. The 3mm diameter coil is wound from a melt-extracted amorphous Co69.25Fe4.25Si13B12.5Nb1 microwire. Unlike typical solenoids, the MMC is sensitive to small magnetic fields due to a significant change in an impedance attributed to the high-frequency giant magneto-impedance (GMI) effect. We propose an application of the MMC sensor to detect a position-varying source of a small magnetic field (∼0.01–10Oe) for real-time respiratory monitoring of a human patient. We simulate this application by mounting a small permanent magnet to a mechanical vibrator and vibrating the magnet at different frequencies, amplitudes, and waveforms ∼3–15cm above the MMC. This newly developed MMC magneto-LC resonance technology is highly promising for active respiratory motion monitoring and other biomedical field sensing applications.

Skin-mountable stretch sensor for wearable health monitoring.

This work presents a wrinkled Platinum (wPt) strain sensor with tunable strain sensitivity for applications in wearable health monitoring. These stretchable sensors show a dynamic range of up to 185% strain and gauge factor (GF) of 42. This is believed to be the highest reported GF of any metal thin film strain sensor over a physiologically relevant dynamic range to date. Importantly, sensitivity and dynamic range are tunable to the application by adjusting wPt film thickness. Performance is reliable over 1000 cycles with low hysteresis after sensor conditioning. The possibility of using such a sensor for real-time respiratory monitoring by measuring chest wall displacement and correlating with lung volume is demonstrated.

Intensity-Modulated Microbend Fiber Optic Sensor for Respiratory Monitoring and Gating During MRI

This paper describes a novel microbend fiber optic sensor system for respiratory monitoring and respiratory gating in the MRI environment. The system enables the noninvasive real-time monitoring and measurement of breathing rate and respiratory/body movement pattern of healthy subjects inside the MRI gantry, and has potential application in respiratory-gated image acquisition based on respiratory cues. The working principle behind this sensor is based on the microbending effect of an optical fiber on light transmission. The sensor system comprises of a 1.0-mm-thin graded-index multimode optical fiber-embedded plastic sensor mat, a photoelectronic transceiver, and a computer with a digital signal processing algorithm. In vitro testing showed that our sensor has a typical signal-to-noise ratio better than 28 dB. Clinical MRI trials conducted on 20 healthy human subjects showed good and comparable breathing rate detection (with an accuracy of ±2 bpm) and respiratory-gated image quality produced using the sensor system, with reference to current predicate hospital device/system. The MRI safe, ease of operation characteristics, low fabrication cost, and extra patient comfort offered by this system suggest its good potential in replacing predicate device/system and serve as a dual function in real-time respiratory monitoring and respiratory-gated image acquisition at the same time during MRI.

Journal-related Activities and Other Special Activities at the 2012 American Society of Anesthesiologists Annual Meeting

Journal-related Activities and Other Special Activities at the 2012 American Society of Anesthesiologists Annual Meeting

Real-time respiration monitoring using the radiotherapy treatment beam and four-dimensional computed tomography (4DCT)—a conceptual study

Real-time knowledge of intra-fraction motion, such as respiration, is essential for four-dimensional (4D) radiotherapy. Surrogate-based and internal-fiducial-based methods may suffer from one or many drawbacks such as false correlation, being invasive, delivering extra patient radiation, and requiring complicated hardware and software development and implementation. In this paper we develop a simple non-surrogate, non-invasive method to monitor respiratory motion during radiotherapy treatments in real time. This method directly utilizes the treatment beam and thus imposes no additional radiation to the patient. The method requires a pre-treatment 4DCT and a real-time detector system. The method combines off-line processes with on-line processes. The off-line processes include 4DCT imaging and pre-calculating detector signals at each phase of the 4DCT based on the planned fluence map and the detector response function. The on-line processes include measuring detector signal from the treatment beam, and correlating the measured detector signal with the pre-calculated signals. The respiration phase is determined as the position of peak correlation. We tested our method with extensive simulations based on a TomoTherapy machine and a 4DCT of a lung cancer patient. Three types of simulations were implemented to mimic the clinical situations. Each type of simulation used three different TomoTherapy delivery sinograms, each with 800 to 1000 projections, as input fluences. Three arbitrary breathing patterns were simulated and two dose levels, 2 Gy/fraction and 2 cGy/fraction, were used for simulations to study the robustness of this method against detector quantum noise. The algorithm was used to determine the breathing phases and this result was compared with the simulated breathing patterns. For the 2 Gy/fraction simulations, the respiration phases were accurately determined within one phase error in real time for most projections of the treatment, except for a few projections at the start and end of the treatment in which beam intensities were extremely low. At 2 cGy/fraction dose level, the method can still determine the respiration phase very well with less than 10% of projections having more than two phases (∼1 s) error. This technique can also be applied in other delivery systems such as orthogonal x-ray systems, although in those cases it would entail the delivery of additional non-treatment radiation.

Real-time respiratory monitoring workstation--software and hardware engineering aspects.

We have applied advanced real-time techniques in software, that are intensively used in critical areas like space research and defence applications, to realise an Integrated Real-Time Respiratory Monitoring System at the Thorax Anesthesiology, Academic Hospital Rotterdam. The system is called the 'SERVO WINDOW'--a window to the servo ventilator. The heart of the system is a real-time kernel that uses preemptive scheduling to achieve multitasking on a IBM PC compatible hardware platform. To the clinician this means that he gets all relevant information from one source i.e. the Respiratory Workstation. The waveforms of the airway pressure, airway flow and the expired CO2 curve are displayed continuously on the screen. The Vector Loops like Pressure Volume, Flow Pressure and Flow Volume loops are also available in addition to the lung mechanics parameters like Expiratory and Inspiratory Resistances, Compliances, Peak Pressure, PEEP, etc. The Single Breath Diagram i.e. expired CO2 concentration versus volume and dead space ventilation is also calculated. The blood gas analysis data is plotted in convenient diagrams like the O2-CO2 diagram, Oxygen Chart, etc. The trend of all these parameters are available with a granularity of one minute. An industry standard laser printer is used for report generation to produce reports of the real-time waveforms, parameter values and the trends. User interface is through easy menus with the traditional keyboard, touchscreen including keyboard on screen for data entry and the mouse.