Cell growth is very important for the development and maintenance of organisms, and it is essential to study factors that affect cell growth, such as gas concentrations that affect cell metabolism, especially oxygen and carbon dioxide. In this study, the dynamic activity of cells according to oxygen concentration was analyzed using a dynamic full-field optical coherence tomography imaging system in a gas-controlled chamber for label-free analysis of living cells. This study aims to understand the relationship between gas supply levels and intracellular activity through non-invasive observation. This discovery could have important implications for biomedicine and biotechnology.
The global outbreak of novel Coronavirus Disease (COVID-19) in 2019 required a method for detecting and continuously monitoring patients with an infectious respiratory disease. Patients infected with acute respiratory disease show symptoms of shallow, rapid breathing and dyspnea due to hypoxia-hypercapnia.
In this paper, we develop a system for monitoring of patients with infectious respiratory disease in real time using NIRS sensors and classifies breathing patterns using deep learning algorithm.
We have developed an integrated wearable to monitor skin temperature, blood and tissue oxygen saturation levels, respiratory rate, and pulse rate. The wearable was tested during different breathing exercises including breath holding, paced breathing, and hypercapnia. Preliminary data showed a consistent agreement between measurements from the wearable with signals measured from a commercial system. In addition, tissue oxygen saturation level measured at the subjects’ chest corresponds better to a breathing exercise than arterial blood oxygen saturation level measured at a fingertip. This result demonstrates the capability of our wearable device in monitoring physiological signs in patients with infectious respiratory diseases.
Humans must keep their bodies' levels of oxygen in balance to stay healthy. Hypoxia, which is common in respiratory illnesses such as pneumonia, the flu, and COVID-19, is a state in which there is insufficient oxygen in the tissues to maintain appropriate homeostasis. Using a customized multimodal biosensor device, the aim of this observational study is to develop a point-of-care method for screening and monitoring individuals with infectious respiratory diseases.
We have developed a wearable and wireless near-infrared spectroscopy (NIRS) device to monitor fetal heart rate and heart rate variability. The device was applied to measure NIRS signals in 12 pregnant volunteers in their second and third trimesters. The fetal heart rate calculated from these NIRS signals is consistent with the fetal heart rate measured from a continuous Doppler ultrasound device. This result suggests a potential of a wireless, wearable, and affordable device to monitor fetal well-being continuously. If successful, this device will be extremely helpful to low-income populations who have limited access to modern healthcare.
The COVID-19 outbreak in 2019 is still a pandemic due to its strong contagiousness and viability. In order to prevent the spread of COVID-19, a non-contact monitoring system is needed. COVID-19 patients show symptoms similar to acute viral pneumonia. Because of this, COVID-19 patients are characterized by faster and shallower breathing than normal people. These respiratory status changes affect tissue oxygenation status. In this paper, we develop a system for monitoring changes in tissue oxygenation status in real time using NIRS sensors and classifies breathing patterns using deep learning algorithm.
KEYWORDS: Near infrared spectroscopy, Tissues, Tissue optics, Near infrared, Oxygen, Spectroscopy, Oximetry, Monte Carlo methods, Light sources, Spectroscopes
In this study, we propose a new approach to measuring tissue oxygenation with near-infrared spectroscopy using a single source-detector separation. This method is based on the difference in absorbance at three wavelengths before, at, and after the isosbestic point. The accuracy of tissue oxygenation measurement using the multiwavelength method was tested using Monte Carlo simulation and spatially resolved spectroscopy. Tissue oxygenation calculated from a single source-detector separation using multiwavelength was similar to one calculated from two source-detector separations using the spatially resolved method. This suggested method can help to simplify a tissue oximeter.
Dynamic full-field optical coherence microscopy (DFFOCM) was used to characterize the intracellular dynamic activities and cytoskeleton of HeLa cells in different viability states. HeLa cell samples were continuously monitored for 24 hours and compared with histological examination to confirm the cell viability states. The averaged mean frequency and magnitude observed in healthy cells were 4.79±0.5 Hz and 2.44±1.06, respectively. In dead cells, the averaged mean frequency was shifted to 8.57±0.71 Hz, whereas the magnitude was significantly decreased to 0.53±0.25. This cell dynamic activity analysis using DFFOCM is expected to replace conventional time-consuming and biopsies-required histological or biochemical methods.
A non-invasive, wearable Near Infrared Spectroscopy (NIRS) device was designed to measure in-vivo placental oxygenation. The device was used in a preliminary study in 12 healthy, singleton, pregnant volunteers at week 33.3±3.6 pregnancy. At postpartum, the placentas from 10 patients were then sent to a pathology lab, where five of them were found to have lesions. Placentas with lesions have significantly lower oxygenation levels (68.7% ± 5.6%) than the ones without lesions (74.2% ± 5.8%). This wearable NIRS device can be a potential point-of-care device to non-invasively check the lesion status of a placenta antepartum.
Purpose: The recent coronavirus disease 2019 (COVID-19) pandemic, which spread across the globe in a very short period of time, revealed that the transmission control of disease is a crucial step to prevent an outbreak and effective screening for viral infectious diseases is necessary. Since the severe acute respiratory syndrome (SARS) outbreak in 2003, infrared thermography (IRT) has been considered a gold standard method for screening febrile individuals at the time of pandemics. The objective of this review is to evaluate the efficacy of IRT for screening infectious diseases with specific applications to COVID-19.
Approach: A literature review was performed in Google Scholar, PubMed, and ScienceDirect to search for studies evaluating IRT screening from 2002 to present using relevant keywords. Additional literature searches were done to evaluate IRT in comparison to traditional core body temperature measurements and assess the benefits of measuring additional vital signs for infectious disease screening.
Results: Studies have reported on the unreliability of IRT due to poor sensitivity and specificity in detecting true core body temperature and its inability to identify asymptomatic carriers. Airport mass screening using IRT was conducted during occurrences of SARS, Dengue, Swine Flu, and Ebola with reported sensitivities as low as zero. Other studies reported that screening other vital signs such as heart and respiratory rates can lead to more robust methods for early infection detection.
Conclusions: Studies evaluating IRT showed varied results in its efficacy for screening infectious diseases. This suggests the need to assess additional physiological parameters to increase the sensitivity and specificity of non-invasive biosensors.
A non-destructive elastic properties detection method based on 3×3 fiber-optic coupler based interferometer is proposed. The relationship of speed versus frequency components of surface acoustic wave (SAW) propagating through the surface of an object gives clues of its physical properties such as elasticity, density, and thickness, etc. In order to reliably observe the SAW signals of objects where physical contact is not allowed, we constructed an interferometer based on the fiber-optic coupler and measured the SAW signal. The performance of the system was verified with well-defined layer phantoms which were made in various structures and analyzed the elasticity and structure of the samples.
We have developed a wearable Near Infrared Spectroscopy (NIRS) device to measure the placental oxygenation. The device comprises of six source-detector distances to probe the oxygenation at different tissues. We have measured NIRS signals and tissue thickness in 12 healthy, singleton, pregnant volunteers (week 33.3±3.6 pregnancy). The placental oxygenation calculated for this group ranges from 68% to 89%. However, we found that the calculated placental oxygenation is positively correlated with the thickness of the fat layer. Hence, we are now performing a Monte Carlo simulation on a five-layer model to correct the effect of fat on placental oxygenation.
This study suggests a new approach to examine mirror neuron network (MNN) using Near-Infrared Spectroscopy (NIRS). Instead of looking at the averaged cerebral hemodynamic change during the action-observation and action-execution, we correlated the connectivity during the tasks across all subjects. We found 8 within region connections and 7 between regions connections in the precentral, postcentral, angular, and parietal lobes, which can be part of the MNN. These connections satisfy conditions of having a strong connectivity in both action-observation and action-execution task and a significant correlation between the connectivity during both tasks. This study results are consistent with previous studies.
Significance: Placenta is an essential organ for fetal development and successful reproduction. Placental insufficiency can lead to fetal hypoxia and, in extreme cases anoxia, leading to fetal death. Of the 145 million deliveries per year worldwide, ∼15 million neonates are small for gestational age and, therefore, at risk for antepartum and intrapartum hypoxia. Clinical methods to assess placental function largely rely on the assessment of fetal heart rate changes but do not assess placental oxygenation. Near-infrared spectroscopy (NIRS) allows non-invasive, real-time assessment of tissue oxygenation in intact organs, which can be used to assess placental oxygenation. However, tissue optical properties can affect the accuracy of methods to measure tissue oxygenation.
Aim: This study was performed to estimate the scattering coefficient of the human placenta. We have computed the scattering coefficients of the human placenta for the range of 659 to 840 nm using two methods of diffuse reflectance spectroscopy (DRS).
Approach: Measurements were performed using an in-house DRS device and a well-established frequency-domain diffuse optical spectroscopic system (DOSI). Measurements were performed in eight placentas obtained after cesarean deliveries. Placentas were perfused with normal saline to minimize the effects of absorption due to blood. Three sites per placenta were measured. Absorption and scattering coefficients were then calculated from the measured reflectance using the random walk theory for DRS and frequency-domain algorithm for DOSI.
Results: Average reduced scattering coefficient (μs ′ ) was 0.943 ± 0.015 mm − 1 at 760 nm and 0.831 ± 0.009 mm − 1 at 840 nm, and a power function μs ′ = 1.6619 (λ/500 nm) − 1.426 was derived for the human placental scattering coefficient.
Conclusion: We report for the first time the scattering coefficient of the human placenta. This information can be used to assess baseline scattering and improve measurements of placental oxygen saturation with NIRS.
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