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The performance of a pulse oximeter based on photoelectric detection is greatly affected by motion noise (MA) in the photoplethysmographic (PPG) signal. This paper presents an algorithm for detecting motion oxygen saturation, which reconstructs a motion noise reference signal using ensemble of complete adaptive noise and empirical mode decomposition combined with multi-scale permutation entropy, and eliminates MA in the PPG signal using a convex combination least mean square adaptive filters to calculate dynamic oxygen saturation. The test results show that, under simulated walking and jogging conditions, the mean absolute error (MAE) of oxygen saturation estimated by the proposed algorithm and the reference oxygen saturation are 0.05 and 0.07, respectively, with means absolute percentage error (MAPE) of 0.05% and 0.07%, respectively. The overall Pearson correlation coefficient reaches 0.971 2. The proposed scheme effectively reduces motion artifacts in the corrupted PPG signal and is expected to be applied in portable photoelectric pulse oximeters to improve the accuracy of dynamic oxygen saturation measurement.

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Significance: Imaging blood oxygen saturation ( SO 2 ) in the skin can be of clinical value when studying ischemic tissue. Emerging multispectral snapshot cameras enable real-time imaging but are limited by slow analysis when using inverse Monte Carlo (MC), the gold standard for analyzing multispectral data. Using artificial neural networks (ANNs) facilitates a significantly faster analysis but requires a large amount of high-quality training data from a wide range of tissue types for a precise estimation of SO 2 . Aim: We aim to develop a framework for training ANNs that estimates SO 2 in real time from multispectral data with a precision comparable to inverse MC. Approach: ANNs are trained using synthetic data from a model that includes MC simulations of light propagation in tissue and hardware characteristics. The model includes physiologically relevant variations in optical properties, unique sensor characteristics, variations in illumination spectrum, and detector noise. This approach enables a rapid way of generating high-quality training data that covers different tissue types and skin pigmentation. Results: The ANN implementation analyzes an image in 0.11 s, which is at least 10,000 times faster than inverse MC. The hardware modeling is significantly improved by an in-house calibration of the sensor spectral response. An in-vivo example shows that inverse MC and ANN give almost identical SO 2 values with a mean absolute deviation of 1.3%-units. Conclusions: ANN can replace inverse MC and enable real-time imaging of microcirculatory SO 2 in the skin if detailed and precise modeling of both tissue and hardware is used when generating training data.

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It is not easy to determine the time between diagnosis and inflammation in patients with type 2 diabetes foot disease. In severe cases, it can lead to ulceration or even amputation. During the development of the inflammation, there will be changes in temperature and blood oxygen saturation in the sole of the foot. Therefore, early monitoring can be an effective prevention and reminder. By integrating flexible conductive fibres, conductive ink and fabric, six nodes on the sole of the foot are monitored. Blood oxygen is monitored above the thumb using photoelectric sensors. The monitoring data signals from these two areas are transmitted to the integrated sensor on the top of the socks and then to the mobile app via Bluetooth. Blood oxygen saturation and temperature can be displayed in real time, and the data is also uploaded to ports such as doctors, communities and hospitals for clinical diagnosis. This study can effectively monitor and remind the inflammatory changes after diabetic foot disease, and change the way of health monitoring by design. Although this study does not have the function of treatment, it is the greatest value of designing intervention medical health - prevention reminder.

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Obstructive sleep apnea [OSA] is widespread in the population and affects as many as one billion people worldwide. OSA is associated with dysfunction of the brain system that controls breathing, which leads to intermittent hypoxia [IH], hypercapnia, and oxidative stress [OS]. The number of NOD-like receptor family pyrin domain-containing [NLRP3] inflammasome was increased after IH, hypercapnia, and OS. NLRP3 inflammasome is closely related to inflammation. NLRP3 inflammasome causes a series of inflammatory diseases by activating IL-1ß and IL-18. Subsequently, NLRP3 inflammasome plays an important role in the complications of OSA, including Type 2 diabetes [T2DM], coronary heart disease [CHD], hypertension, neuroinflammation, and depression. This review will introduce the basic composition and structure of the NLRP3 inflammasome and focus on the relationship between the NLRP3 inflammasome and OSA and OSA complications. We can deeply understand how NLRP3 inflammasome is strongly associated with OSA and OSA complications.

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Blood oxygen saturation (SpO2) is an essential physiological parameter for evaluating a person's health. While conventional SpO2 measurement devices like pulse oximeters require skin contact, advanced computer vision technology can enable remote SpO2 monitoring through a regular camera without skin contact. In this paper, we propose novel deep learning models to measure SpO2 remotely from facial videos and evaluate them using a public benchmark database, VIPL-HR. We utilize a spatial-temporal representation to encode SpO2 information recorded by conventional RGB cameras and directly pass it into selected convolutional neural networks to predict SpO2. The best deep learning model achieves 1.274% in mean absolute error and 1.71% in root mean squared error, which exceed the international standard of 4% for an approved pulse oximeter. Our results significantly outperform the conventional analytical Ratio of Ratios model for contactless SpO2 measurement. Results of sensitivity analyses of the influence of spatial-temporal representation color spaces, subject scenarios, acquisition devices, and SpO2 ranges on the model performance are reported with explainability analyses to provide more insights for this emerging research field.

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Hyperspectral Imaging (HSI) seamlessly integrates imaging and spectroscopy, capturing both spatial and spectral data concurrently. With widespread applications in medical diagnostics, HSI serves as a noninvasive tool for gaining insights into tissue characteristics. The distinctive spectral profiles of biological tissues set HSI apart from traditional microscopy in enabling in vivo tissue analysis. Despite its potential, existing HSI techniques face challenges such as alignment issues, low light throughput, and tissue heating due to intense illumination. This study introduces an innovative HSI system featuring active sequential bandpass illumination seamlessly integrated into conventional optical instruments. The primary focus is on analyzing oxyhemoglobin and deoxyhemoglobin saturation in animal tissue samples using multivariate linear regression. This approach holds promise for enhancing noninvasive medical diagnostics. A key feature of the system, active bandpass illumination, effectively prevents tissue overheating, thereby bolstering its suitability for medical applications.

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Despite the large impact chronic obstructive pulmonary disease (COPD) that has on the population, the implementation of new technologies for diagnosis and treatment remains limited. Current practices in ambulatory oxygen therapy used in COPD rely on fixed doses overlooking the diverse activities which patients engage in. To address this challenge, we propose a software architecture aimed at delivering patient-personalized edge-based artificial intelligence (AI)-assisted models that are built upon data collected from patients' previous experiences along with an evaluation function. The main objectives reside in proactively administering precise oxygen dosages in real time to the patient (the edge), leveraging individual patient data, previous experiences, and actual activity levels, thereby representing a substantial advancement over conventional oxygen dosing. Through a pilot test using vital sign data from a cohort of five patients, the limitations of a one-size-fits-all approach are demonstrated, thus highlighting the need for personalized treatment strategies. This study underscores the importance of adopting advanced technological approaches for ambulatory oxygen therapy.

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Alzheimer's disease (AD) is the most common neurodegenerative disorder with the pathological hallmarks of amyloid beta (Aß) plaques and neurofibrillary tangles (NFTs) in the brain. Although there is a hope that anti-amyloid monoclonal antibodies may emerge as a new therapy for AD, the high cost and side effect is a big concern. Non-drug therapy is attracting more attention and may provide a better resolution for the treatment of AD. Given the fact that hypoxia contributes to the pathogenesis of AD, hyperbaric oxygen therapy (HBOT) may be an effective intervention that can alleviate hypoxia and improve AD. However, it remains unclear whether long-term HBOT intervention in the early stage of AD can slow AD progression and ultimately prevent cognitive impairment in this disease. In this study we applied consecutive 3-month HBOT interventions on 3-month-old APPswe/PS1dE9 AD mice which represent the early stage of AD. When the APPswe/PS1dE9 mice at 9-month-old which represent the disease stage we measured cognitive function, 24-h blood oxygen saturation, Aß and tau pathologies, vascular structure and function, and neuroinflammation in APPswe/PS1dE9 mice. Our results showed that long-term HBOT can attenuate the impairments in cognitive function observed in 9-month-old APPswe/PS1dE9 mice. Most importantly, HBOT effectively reduced the progression of Aß plaques deposition, hyperphosphorylated tau protein aggregation, and neuronal and synaptic degeneration in the AD mice. Further, long-term HBOT was able to enhance blood oxygen saturation level. Besides, long-term HBOT can improve vascular structure and function, and reduce neuroinflammation in AD mice. This study is the first to demonstrate that long-term HBOT intervention in the early stage of AD can attenuate cognitive impairment and AD-like pathologies. Overall, these findings highlight the potential of long-term HBOT as a disease-modifying approach for AD treatment.

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OBJECTIVE:Masks are one of the most important defenses against the virus.However,the impact of wearing masks during daily activities or sports on respiratory and circulatory function remains controversial.A comprehensive quantitative evaluation of the effects of mask-wearing on human heart rate,oxygen saturation and end-expiratory carbon dioxide by Meta-analysis was conducted.The effects of wearing different types of masks at different exercise intensities and time of exercise on the human respiratory and circulatory system were explored. METHODS:By February 2023,with"mask,face mask,N95,training,sports,running,walking,cycling"as the Chinese search terms and"masks,respiratory protective devices,N95 respirators,surgical face masks,exercise,resistance training,explosive training,muscle exercises"as English search terms,the experimental studies addressing the influence of exercise with a mask on hemodynamic indexes were retrieved from CNKI,Web of Science,PubMed,Cochrane Library and WanFang databases.The outcome indicators included three continuous variables-exercise center rate,blood oxygen saturation and end-expiratory carbon dioxide.Stata16.0 software was used to analyze the outcome indicators of the included literature.The PEDro scale was used as a quality assessment tool,and the funnel plot was used to analyze the impact of publication bias. RESULTS:Totally 25 articles involving 857 healthy children and adults were included in this Meta-analysis.The overall methodological quality was high,with 22 studies scoring 6 points on the PEDro scale,2 studies scoring 7 points and 1 study scoring 8 points.The meta-analysis results showed that compared with the control group,exercise with masks had no significant effect on heart rate(SMD=0.02,95%CI:-0.11 to 0.15,P=0.81),but increased end-expiratory carbon dioxide(SMD=0.60,95%CI:0.37 to 0.83,P=0.00),decreased oxygen saturation(SMD=-0.28,95%CI:-0.47 to-0.09,P=0.03).Intensity and duration were the factors that affected the heterogeneity between studies.Wearing a mask during high-intensity exercise significantly increased heart rate(SMD=-0.20,95%CI:-0.36 to-0.04,P=0.02).The effect of high-intensity and short-time exercise on blood oxygen saturation was significantly higher than that of other exercises(SMD=-0.40,95%CI:-0.70 to-0.10;SMD=-0.25,95%CI:-0.45 to-0.04).For end-expiratory carbon dioxide,maintaining a certain intensity and increasing the exercise time or increasing the intensity further increased the index significantly,reaching a moderate effect size(SMD=0.61,95%CI:0.06 to 1.15;SMD=0.58,95%CI:0.04 to 1.13). CONCLUSION:Existing evidence suggests that exercise with masks may have the adverse effect of increasing end-expiratory carbon dioxide and decreasing blood oxygen saturation.The influence of different exercise test time and intensities on the three outcome indexes was different.Wearing a mask during high-intensity exercise can significantly increase heart rate and decrease blood oxygen saturation.Maintaining moderate intensity for a long period or further increasing the intensity of exercise will lead to increased end-expiratory carbon dioxide levels.

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Introduction: Respiratory diseases such as chronic obstructive pulmonary disease, obstructive sleep apnea syndrome, and COVID-19 may cause a decrease in arterial oxygen saturation (SaO2). The continuous monitoring of oxygen levels may be beneficial for the early detection of hypoxemia and timely intervention. Wearable non-invasive pulse oximetry devices measuring peripheral oxygen saturation (SpO2) have been garnering increasing popularity. However, there is still a strong need for extended and robust clinical validation of such devices, especially to address topical concerns about disparities in performances across racial groups. This prospective clinical validation aimed to assess the accuracy of the reflective pulse oximeter function of the EmbracePlus wristband during a controlled hypoxia study in accordance with the ISO 80601-2-61:2017 standard and the Food & Drug Administration (FDA) guidance. Methods: Healthy adult participants were recruited in a controlled desaturation protocol to reproduce mild, moderate, and severe hypoxic conditions with SaO2 ranging from 100% to 70% (ClinicalTrials.gov registration #NCT04964609). The SpO2 level was estimated with an EmbracePlus device placed on the participant's wrist and the reference SaO2 was obtained from blood samples analyzed with a multiwavelength co-oximeter. Results: The controlled hypoxia study yielded 373 conclusive measurements on 15 subjects, including 30% of participants with dark skin pigmentation (V-VI on the Fitzpatrick scale). The accuracy root mean square (Arms) error was found to be 2.4%, within the 3.5% limit recommended by the FDA. A strong positive correlation between the wristband SpO2 and the reference SaO2 was observed (r = 0.96, P < 0.001), and a good concordance was found with Bland-Altman analysis (bias, 0.05%; standard deviation, 1.66; lower limit, -4.7%; and upper limit, 4.8%). Moreover, acceptable accuracy was observed when stratifying data points by skin pigmentation (Arms 2.2% in Fitzpatrick V-VI, 2.5% in Fitzpatrick I-IV), and sex (Arms 1.9% in females, and 2.9% in males). Discussion: This study demonstrates that the EmbracePlus wristband could be used to assess SpO2 with clinically acceptable accuracy under no-motion and high perfusion conditions for individuals of different ethnicities across the claimed range. This study paves the way for further accuracy evaluations on unhealthy subjects and during prolonged use in ambulatory settings.

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Monitoring and analysis of anesthesia depth status data refers to evaluating the anesthesia depth status of patients during the surgical process by monitoring their physiological index data, and conducting analysis and judgment. The depth of anesthesia is crucial for the safety and success of the surgical process. By monitoring the state of anesthesia depth, abnormal conditions of patients can be detected in a timely manner and corresponding measures can be taken to prevent accidents from occurring. Traditional anesthesia monitoring methods currently include computer tomography, electrocardiogram, respiratory monitoring, etc. In this regard, traditional physiological indicator monitoring methods have certain limitations and cannot directly reflect the patient's neural activity status. The monitoring and analysis methods based on neuroscience can obtain more information from the level of brain neural activity. PURPOSE: In this article, the monitoring and analysis of anesthesia depth status data would be studied through neuroscience. METHODS: Through a controlled experiment, the monitoring accuracy of traditional anesthesia status monitoring algorithm and neuroscience-based anesthesia status monitoring algorithm was studied, and the information entropy and oxygen saturation of electroencephalogram signals in patients with different anesthesia depth were explored. RESULTS: The experiment proved that the average monitoring accuracy of the traditional anesthesia state monitoring algorithm in patients' blood drug concentration and oxygen saturation reached 95.55 and 95.00%, respectively. In contrast, the anesthesia state monitoring algorithm based on neuroscience performs better, with the average monitoring accuracy of drug concentration and oxygen saturation reaching 98.00 and 97.09%, respectively. This experimental result fully proved that the monitoring performance of anesthesia state monitoring algorithms based on neuroscience is better. CONCLUSION: The experiment proved the powerful monitoring ability of the anesthesia state monitoring algorithm based on neuroscience used in this article, and explained the changing trend of brain nerve signals and oxygen saturation of patients with different anesthesia depth states, which provided a new research method for the monitoring and analysis technology of anesthesia depth state data.

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Delayed treatment of testicular torsion (TT) can lead to permanent loss of reproductive capacity. Photoacoustic imaging (PAI) and ultrasound imaging (USI) was tested for detecting TT at early stage in mice based on PAI-obtained oxygen saturation (sO2), and USI-collected color pixel density (CPD), peak systolic velocity (PSV) and resistance index (RI). For complete TT, both CPD (9.08 % ± 3.084 to almost zero) and sO2 data (70.09 % ± 1.656-59.84 % ± 1.427) showed an significant change 2 h post-torsion. For incomplete TT, sO2 data exhibited a strong time relationship (Mean values: 6 h, 64.83 % ± 1.898; 12 h, 60.67 % ± 3.555; 24 h, 57.85 % ± 3.575; P < 0.05). However, USI-collected CPD, PSV or IR data from the same TT models showed no significant difference. This study indicated that USI and PAI could identify complete TT. Meanwhile, PAI has shown great potential in the diagnosis of incomplete TT within 24 h based on time-related sO2 map.

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Since the outbreak of COVID-19, as of January 2023, there have been over 670 million cases and more than 6.8 million deaths worldwide. Infections can cause inflammation in the lungs and decrease blood oxygen levels, which can lead to breathing difficulties and endanger life. As the situation continues to escalate, non-contact machines are used to assist patients at home to monitor their blood oxygen levels without encountering others. This paper uses a general network camera to capture the forehead area of a person's face, using the RPPG (remote photoplethysmography) principle. Then, image signal processing of red and blue light waves is carried out. By utilizing the principle of light reflection, the standard deviation and mean are calculated, and the blood oxygen saturation is computed. Finally, the effect of illuminance on the experimental values is discussed. The experimental results of this paper were compared with a blood oxygen meter certified by the Ministry of Health and Welfare in Taiwan, and the experimental results had only a maximum error of 2%, which is better than the 3% to 5% error rates in other studies The measurement time was only 30 s, which is better than the one minute reported using similar equipment in other studies. Therefore, this paper not only saves equipment expenses but also provides convenience and safety for those who need to monitor their blood oxygen levels at home. Future applications can combine the SpO2 detection software with camera-equipped devices such as smartphones and laptops. The public can detect SpO2 on their own mobile devices, providing a convenient and effective tool for personal health management.

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Background: Appropriate levels of blood oxygen are crucial for critically ill patients. However, the optimal oxygen saturation has not been confirmed for AECOPD patients during their ICU stays. The purpose of this study was to determine the optimal oxygen saturation range target to reduce mortality for those individuals. Methods: Data of 533 critically ill AECOPD patients with hypercapnic respiratory failure from the MIMIC-IV database were extracted. The association between median SpO2 value during ICU stay and 30days mortality was analyzed by LOWESS curve, and an optimal range of SpO2(92-96%) platform was observed. Comparisons between subgroups and linear analyses of the percentage of SpO2 in 92-96% and 30days or 180 days mortality were performed to support our view further. Methods: Although patients with 92-96% SpO2 had a higher rate of invasive ventilator than those with 88-92%, there was no significant increase in the adjusted ICU stay duration, non-invasive ventilator duration, or invasive ventilator duration while leading to lower 30days and 180days mortality in the subgroup with 92-96%. In addition, the percentage of SpO2 in 92-96% was associated with decreased hospital mortality. Conclusion: In conclusion, SpO2 within 92-96% could lead to lower mortality than 88-92% and > 96% for AECOPD patients during their ICU stay.

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Hemodynamic monitoring in children is challenging for many reasons. Technical limitations in combination with insufficient validation against reference methods, makes reliable monitoring systems difficult to establish. Since recent studies have highlighted perioperative cardiovascular stability as an important factor for patient outcome in pediatrics, the need for accurate hemodynamic monitoring methods in children is obvious. The development of mathematical processing of fast response mainstream capnography signals, has allowed for the development of capnodynamic hemodynamic monitoring. By inducing small changes in ventilation in intubated and mechanically ventilated patients, fluctuations in alveolar carbon dioxide are created. The subsequent changes in carbon dioxide elimination can be used to calculate the blood flow participating in gas exchange, i.e., effective pulmonary blood flow which equals the non-shunted pulmonary blood flow. Cardiac output can then be estimated and continuously monitored in a breath-by-breath fashion without the need for additional equipment, training, or calibration. In addition, the method allows for mixed venous oxygen saturation (SvO2) monitoring, without pulmonary artery catheterization. The current review will discuss the capnodyamic method and its application and limitation as well as future potential development and functions in pediatric patients.

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On average, arterial oxygen saturation measured by pulse oximetry (SpO2) is higher in hypoxemia than the true oxygen saturation measured invasively (SaO2), thereby increasing the risk of occult hypoxemia. In the current article, measurements of SpO2 on 17 cyanotic newborns were performed by means of a Nellcor pulse oximeter (POx), based on light with two wavelengths in the red and infrared regions (660 and 900 nm), and by means of a novel POx, based on two wavelengths in the infrared region (761 and 820 nm). The SpO2 readings from the two POxs showed higher values than the invasive SaO2 readings, and the disparity increased with decreasing SaO2. SpO2 measured using the two infrared wavelengths showed better correlation with SaO2 than SpO2 measured using the red and infrared wavelengths. After appropriate calibration, the standard deviation of the individual SpO2-SaO2 differences for the two-infrared POx was smaller (3.6%) than that for the red and infrared POx (6.5%, p < 0.05). The overestimation of SpO2 readings in hypoxemia was explained by the increase in hypoxemia of the optical pathlengths-ratio between the two wavelengths. The two-infrared POx can reduce the overestimation of SpO2 measurement in hypoxemia and the consequent risk of occult hypoxemia, owing to its smaller increase in pathlengths-ratio in hypoxemia.

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Background & aims  Intracardiac shunts are abnormal channels of blood circulation within the heart that develop either as an additional blood flow pathway or as a replacement for the normal channels of blood circulation. They are the commonest types of congenital heart defects. Various methods are available in the present times to identify, localize or quantify left-to-right intracardiac shunts. Methods may vary in sensitivity, indicators, or types of equipment available. One such method used in almost all cardiac centers for a long time has been oximetry run to detect step-up differences in oxygen saturation values. In the oximetry run the main approach to detect and estimate the left-to-right (L-->R) shunts requires the oxygen concentration expressed as a proportion of saturation to be evaluated in blood samples which are obtained from the right atrium (RA) and pulmonary artery (PA), respectively. A left-to-right shunt can be considered if there is a significant increase (step-up) in blood saturation. A significant step-up is defined as a substantial rise in blood oxygen content or saturation that is higher than normal values. Methods  Using a prospective observational design, this article investigates the application of the step-up method in detecting intracardiac shunts. The study was conducted between 2021 and 2022 on 35 pediatric cardiac patients (males/females, 24/11) diagnosed with post-tricuspid shunts. The pulmonary artery and right atrium were sampled before and after cardiopulmonary bypass surgery and analyzed using a blood gas test. As a result, nearly 91% of the patients had a saturation below 8%. However, the difference between PA oxygen saturation (SO2) & RASO2 before and after surgery was significant. As a result, the difference in O2 saturation helped detect the residual ventricular septal defect (VSD) after the surgery. Results  There were no deaths or complications in this study. There were no re-interventions for post-tricuspid shunt surgery, though one patient had a step-up of >15% and residual VSD status was moderate to large on two-dimensional (2D) echocardiography. Conclusion A combination of physical findings, chest radiography, electrocardiogram (ECG), and echocardiography is routinely done for all these patients undergoing pediatric cardiac surgery. Echocardiography can detect the occurrence of shunt but does not calculate the shunt ratio. Transesophageal or epicardial echocardiography is the standard of care but has its limitations like perception difference between the operating surgeon and the person performing echocardiography. In this study, we have added an oximetry analysis of blood-gas samples before and after surgery and compared it to 2D echocardiography to test the validation of oximetry in isolation and comparison to 2D echocardiography.

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MHealth technologies play a fundamental role in epidemiological situations such as the ongoing outbreak of COVID-19 because they allow people to self-monitor their health status (e.g. vital parameters) at any time and place, without necessarily having to physically go to a medical clinic. Among vital parameters, special care should be given to monitor blood oxygen saturation (SpO2), whose abnormal values are a warning sign for potential COVID-19 infection. SpO2 is commonly measured through the pulse oximeter that requires skin contact and hence could be a potential way of spreading contagious infections. To overcome this problem, we have recently developed a contact-less mHealth solution that can measure blood oxygen saturation without any contact device but simply processing short facial videos acquired by any common mobile device equipped with a camera. Facial video frames are processed in real-time to extract the remote photoplethysmographic signal useful to estimate the SpO2 value. Such a solution promises to be an easy-to-use tool for both personal and remote monitoring of SpO2. However, the use of mobile devices in daily situations holds some challenges in comparison to the controlled laboratory scenarios. One main issue is the frequent change of perspective viewpoint due to head movements, which makes it more difficult to identify the face and measure SpO2. The focus of this work is to assess the robustness of our mHealth solution to head movements. To this aim, we carry out a pilot study on the benchmark PURE dataset that takes into account different head movements during the measurement. Experimental results show that the SpO2 values obtained by our solution are not only reliable, since they are comparable with those obtained with a pulse oximeter, but are also insensitive to head motion, thus allowing a natural interaction with the mobile acquisition device.

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@#Abstract: Objective　To explore the clinical characteristics of nucleic acid negative newborns delivered by pregnant women infected with SARS-CoV-2 (Omicron variant BA. 5.1.3) in Sanya area, and to provide evidence for understanding its clinical characteristics. Methods　A retrospective analysis was performed on 14 neonates with negative nucleic acid delivered by pregnant women who tested positive for SARS-CoV-2 (Omicron variant BA.5.1.3) in Sanya Central Hospital (the Third People's Hospital of Hainan Province) from June 2022 to September 2022 (observation group, n=14). The corresponding nucleic acid-negative newborns delivered by pregnant women detected negative with SARS-CoV-2 (Omicronon variant strain BA.5.1.3) were set as the control group (n=56), and the general data and clinical characteristics of neonates in the two groups were compared. Results　There was no significant difference between the observation group and the control group in pregnancy diabetes, pregnancy induced hypertension, gestational pre-eclampsia, fetal intrauterine distress, premature rupture of membranes (P>0.05); there was no significant difference between the observation group and the control group in terms of sex, gestational age, birth weight, age, mode of delivery, birth Apgar score, heart screening, pulmonary disease, glucose 6-phosphate dehydrogenase (G6PD) deficiency, thalassemia, breast milk jaundice, hemolytic jaundice (P>0.05). The bilirubin level, blue light irradiation cases and the duration of blue light irradiation of the newborns in the observation group at 7 days after birth were higher than those in the control group (P<0.05); the ratio of blood oxygen saturation ≥ 90% in the observation group was lower than that in the control group (21.43% vs 89.29%, P<0.05), and the ratio of blood oxygen saturation occasionally<90% was higher than that in the control group (57.14% vs 10.71%, P<0.05). The ratio of blood oxygen saturation<90% had no significant difference compared with that in the control group (7.14% vs 0, P>0.05), and the ratio of blood oxygen saturation reduced to the required oxygen uptake was higher than that in the control group (14.29% vs 0, P<0.05). Conclusions　The jaundice manifestation of the nucleic acid-negative newborns delivered by pregnant women infected with SARS-CoV-2 (Omicronon variant strain BA.5.1.3) in Sanya area is relatively obvious, with blood oxygen saturation easily lower than 90% and even requiring oxygen inhalation in severe cases.