Innovative Predictive Approach towards a Personalized Oxygen Dosing System.

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.

Overestimation of Oxygen Saturation Measured by Pulse Oximetry in Hypoxemia. Part 1: Effect of Optical Pathlengths-Ratio Increase.

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.

Using machine learning to determine the correlation between physiological and environmental parameters and the induction of acute mountain sickness.

BACKGROUND: Recent studies on acute mountain sickness (AMS) have used fixed-location and fixed-time measurements of environmental and physiological variable to determine the influence of AMS-associated factors in the human body. This study aims to measure, in real time, environmental conditions and physiological variables of participants in high-altitude regions to develop an AMS risk evaluation model to forecast prospective development of AMS so its onset can be prevented. RESULTS: Thirty-two participants were recruited, namely 25 men and 7 women, and they hiked from Cuifeng Mountain Forest Park parking lot (altitude: 2300 m) to Wuling (altitude: 3275 m). Regression and classification machine learning analyses were performed on physiological and environmental data, and Lake Louise Acute Mountain Sickness Scores (LLS) to establish an algorithm for AMS risk analysis. The individual R2 coefficients of determination between the LLS and the measured altitude, ambient temperature, atmospheric pressure, relative humidity, climbing speed, heart rate, blood oxygen saturation (SpO2), heart rate variability (HRV), were 0.1, 0.23, 0, 0.24, 0, 0.24, 0.27, and 0.35 respectively; incorporating all aforementioned variables, the R2 coefficient is 0.62. The bagged trees classifier achieved favorable classification results, yielding a model sensitivity, specificity, accuracy, and area under receiver operating characteristic curve of 0.999, 0.994, 0.998, and 1, respectively. CONCLUSION: The experiment results indicate the use of machine learning multivariate analysis have higher AMS prediction accuracies than analyses utilizing single varieties. The developed AMS evaluation model can serve as a reference for the future development of wearable devices capable of providing timely warnings of AMS risks to hikers.

The accuracy of pulse oximetry in measuring oxygen saturation by levels of skin pigmentation: a systematic review and meta-analysis.

BACKGROUND: During the COVID-19 pandemic, there have been concerns regarding potential bias in pulse oximetry measurements for people with high levels of skin pigmentation. We systematically reviewed the effects of skin pigmentation on the accuracy of oxygen saturation measurement by pulse oximetry (SpO2) compared with the gold standard SaO2 measured by CO-oximetry. METHODS: We searched Ovid MEDLINE, Ovid Embase, EBSCO CINAHL, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform (up to December 2021) for studies with SpO2-SaO2 comparisons and measuring the impact of skin pigmentation or ethnicity on pulse oximetry accuracy. We performed meta-analyses for mean bias (the primary outcome in this review) and its standard deviations (SDs) across studies included for each subgroup of skin pigmentation and ethnicity and used these pooled mean biases and SDs to calculate accuracy root-mean-square (Arms) and 95% limits of agreement. The review was registered with the Open Science Framework ( https://osf.io/gm7ty ). RESULTS: We included 32 studies (6505 participants): 15 measured skin pigmentation and 22 referred to ethnicity. Compared with standard SaO2 measurement, pulse oximetry probably overestimates oxygen saturation in people with the high level of skin pigmentation (pooled mean bias 1.11%; 95% confidence interval 0.29 to 1.93%) and people described as Black/African American (1.52%; 0.95 to 2.09%) (moderate- and low-certainty evidence). The bias of pulse oximetry measurements for people with other levels of skin pigmentation or those from other ethnic groups is either more uncertain or suggests no overestimation. Whilst the extent of mean bias is small or negligible for all subgroups evaluated, the associated imprecision is unacceptably large (pooled SDs > 1%). When the extent of measurement bias and precision is considered jointly, pulse oximetry measurements for all the subgroups appear acceptably accurate (with Arms < 4%). CONCLUSIONS: Pulse oximetry may overestimate oxygen saturation in people with high levels of skin pigmentation and people whose ethnicity is reported as Black/African American, compared with SaO2. The extent of overestimation may be small in hospital settings but unknown in community settings. REVIEW PROTOCOL REGISTRATION: https://osf.io/gm7ty.

In-hospital mortality and SpO2 incritical care patients with cerebral injury: data from the MIMIC­IV Database.

BACKGROUND: Evidence regarding the relationship between in-hospital mortality and SpO2 was low oxygen saturations are often thought to be harmful, new research in patients with brain damage has found that high oxygen saturation actually enhances mortality. However, there is currently no clear study to point out the appropriate range for oxygen saturation in patients with craniocerebral diseases.  METHODS: By screening all patients in the MIMIC IV database, 3823 patients with craniocerebral diseases (according to ICD-9 codes and ICD-10) were selected, and non-linear regression was used to analyze the relationship between in-hospital mortality and oxygen saturation. Covariates for all patients included age, weight, diagnosis, duration of ICU stay, duration of oxygen therapy, etc. RESULTS: In-hospital mortality in patients with TBI and SAH was kept to a minimum when oxygen saturation was in the 94-96 range. And in all patients, the relationship between oxygen saturation and in-hospital mortality was U-shaped. Subgroup analysis of the relationship between oxygen saturation and mortality in patients with metabolic encephalopathy and other encephalopathy also draws similar conclusions In-hospital mortality and oxygen saturation were all U-shaped in patients with subarachnoid hemorrhage, metabolic and toxic encephalopathy, cerebral infarction, and other encephalopathy, but the nonlinear regression was statistically significant only in patients with cerebral infarction (p for nonlinearity = 0.002). CONCLUSION: Focusing too much on the lower limit of oxygen saturation and ignoring too high oxygen saturation can also lead to increase in-hospital mortality. For patients with TBI and SAH, maintaining oxygen saturation at 94-96% will minimize the in-hospital mortality of patients.

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea.

The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) that have led to the search for artificial intelligence-based alternatives. Many classic machine learning methods have been already evaluated for this purpose. In this chapter, we show the main approaches found in the scientific literature along with the most used data to develop the models, useful and large easily available databases, and suitable methods to assess performances. In addition, a range of results from selected studies are presented as examples of these methods. Very high diagnostic performances are reported in these results regardless of the approaches taken. This leads us to conclude that conventional machine learning methods are useful techniques to develop new OSA diagnosis simplification proposals and to act as benchmark for other more recent methods such as deep learning.

Oximetry Indices in the Management of Sleep Apnea: From Overnight Minimum Saturation to the Novel Hypoxemia Measures.

Obstructive sleep apnea (OSA) is a multidimensional disease often underdiagnosed due to the complexity and unavailability of its standard diagnostic method: the polysomnography. Among the alternative abbreviated tests searching for a compromise between simplicity and accurateness, oximetry is probably the most popular. The blood oxygen saturation (SpO2) signal is characterized by a near-constant profile in healthy subjects breathing normally, while marked drops (desaturations) are linked to respiratory events. Parameterization of the desaturations has led to a great number of indices of severity assessment commonly used to assist in OSA diagnosis. In this chapter, the main methodologies used to characterize the overnight oximetry profile are reviewed, from visual inspection and simple statistics to complex measures involving signal processing and pattern recognition techniques. We focus on the individual performance of each approach, but also on the complementarity among the great amount of indices existing in the state of the art, looking for the most relevant oximetric feature subset. Finally, a quick overview of SpO2-based deep learning applications for OSA management is carried out, where the raw oximetry signal is analyzed without previous parameterization. Our research allows us to conclude that all the methodologies (conventional, time, frequency, nonlinear, and hypoxemia-based) demonstrate high ability to provide relevant oximetric indices, but only a reduced set provide non-redundant complementary information leading to a significant performance increase. Finally, although oximetry is a robust tool, greater standardization and prospective validation of the measures derived from complex signal processing techniques are still needed to homogenize interpretation and increase generalizability.

Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal.

Automated analysis of the blood oxygen saturation (SpO2) signal from nocturnal oximetry has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including the detection of respiratory events. However, the few preceding studies using SpO2 recordings have focused on the automated detection of respiratory events versus normal respiration, without making any distinction between apneas and hypopneas. In this sense, the characteristics of oxygen desaturations differ between obstructive apnea and hypopnea episodes. In this chapter, we use the SpO2 signal along with a convolutional neural network (CNN)-based deep-learning architecture for the automatic identification of apnea and hypopnea events. A total of 398 SpO2 signals from adult OSA patients were used for this purpose. A CNN architecture was trained using 30-s epochs from the SpO2 signal for the automatic classification of three classes: normal respiration, apnea, and hypopnea. Then, the apnea index (AI), the hypopnea index (HI), and the apnea-hypopnea index (AHI) were obtained by aggregating the outputs of the CNN for each subject (AICNN, HICNN, and AHICNN). This model showed a promising diagnostic performance in an independent test set, with 80.3% 3-class accuracy and 0.539 3-class Cohen's kappa for the classification of respiratory events. Furthermore, AICNN, HICNN, and AHICNN showed a high agreement with the values obtained from the standard PSG: 0.8023, 0.6774, and 0.8466 intra-class correlation coefficients (ICCs), respectively. This suggests that CNN can be used to analyze SpO2 recordings for the automated diagnosis of OSA in at-home oximetry tests.

MsWH: A Multi-Sensory Hardware Platform for Capturing and Analyzing Physiological Emotional Signals.

This paper presents a new physiological signal acquisition multi-sensory platform for emotion detection: Multi-sensor Wearable Headband (MsWH). The system is capable of recording and analyzing five different physiological signals: skin temperature, blood oxygen saturation, heart rate (and its variation), movement/position of the user (more specifically of his/her head) and electrodermal activity/bioimpedance. The measurement system is complemented by a porthole camera positioned in such a way that the viewing area remains constant. Thus, the user's face will remain centered regardless of its position and movement, increasing the accuracy of facial expression recognition algorithms. This work specifies the technical characteristics of the developed device, paying special attention to both the hardware used (sensors, conditioning, microprocessors, connections) and the software, which is optimized for accurate and massive data acquisition. Although the information can be partially processed inside the device itself, the system is capable of sending information via Wi-Fi, with a very high data transfer rate, in case external processing is required. The most important features of the developed platform have been compared with those of a proven wearable device, namely the Empatica E4 wristband, in those measurements in which this is possible.

Influence of cuff pressures of automatic sphygmomanometers on pulse oximetry measurements.

Information about blood arterial oxygen saturation (SpO2) is crucial in critical care settings or home health monitoring during the COVID-19 pandemic. Also, we need to identify the factors that affect the SpO2 measurement. In this paper, the effect of compression of the cuff during noninvasive blood pressure (NIBP) measurement on the SpO2 results was investigated. A custom-made system was used for simultaneous measurement of NIBP and SpO2. The study was conducted on 213 subjects aged between 21 and 93, with a systolic blood pressure of (94 to 194) mmHg, diastolic blood pressure of (52-98) mmHg, and 994 NIBP readings were used for the analysis. During the NIBP measurement, momentary changes in SpO2 can reach ±17% and are in most cases positive (mean 2.9%). The change was not correlated with sex, age, height, body weight, BMI, HR and blood pressure. The obtained results show that frequent NIBP measurements may lead to wrong conclusions about SpO2. In our study, pressure measurements mainly caused the increase of blood oxygenation level.

Effectiveness of Plasmapheresis Treatment in the Treatment of Patients with COVID-19 Disease.

Background: According to the World Health Organization, COVID-19 management focuses primarily on infection prevention, case management, case monitoring, and supportive care. However, due to the lack of evidence, no specific anti-SARS-CoV-2 treatment is recommended. This study aimed to evaluate the effectiveness of plasmapheresis treatment in COVID-19 patients with symptoms of pulmonary involvement on the computed tomography (CT) of the lung. Methods: In 2021, an experimental study in critically ill patients admitted to the COVID-19 ward in the Hazrat-e Rasool hospital diagnosed with COVID-19 was conducted in the second phase (pilot study). The diagnosis was confirmed according to clinical signs, CT scan of the lung, and the Polymerase chain reaction (PCR) test. All patients received the usual treatments for COVID-19 disease and underwent plasmapheresis at a dose of 40 cc/kg daily up to 4 doses. All patients were observed for 24 hours for complications of plasmapheresis treatment and simultaneously for symptoms of COVID-19, after which only routine care measures were performed. The next day and 2 weeks after resumption of the treatment, patients experienced COVID-19 symptoms, including shortness of breath, cough, and fever. Blood oxygen saturation, and treatment results were evaluated. Qualitative and rank variables were described using absolute and relative frequencies and quantitative parametric variables were used using mean and confidence interval. Frequencies were compared in groups using the chi-square test. All tests were performed in 2 directions and P > 0.05 was considered statistically significant. Results: Of the 120 patients studied, 79 (65.8%) were men and 41 (34.2%) were women. The mean age was 60.30 ± 15.61 years (22-95 years). The mean hospital stay was 12.89 days ± 7.25 days (2-38 days). Increased blood oxygen saturation levels in patients had an increasing trend. Inflammatory indices had a downward trend in patients. The frequency of plasmapheresis had no significant effect on reducing the downward trend of inflammatory markers. The greatest reduction occurred in the first plasmapheresis. Conclusion: Finally, according to the findings, plasmapheresis is one of the appropriate treatments to improve patients' symptoms and reduce cytokine storm. Recovered patients had lower levels of inflammatory markers than those who died.

Sociodemographic determinants and clinical risk factors associated with COVID-19 severity: a cross-sectional analysis of over 200,000 patients in Tehran, Iran.

BACKGROUND: Defining socio-demographic factors, clinical presentations and underlying diseases associated with COVID-19 severity could be helpful in its management. This study aimed to further clarify the determinants and clinical risk factors of the disease severity in patients infected with COVID-19. METHODS: A multi-centre descriptive study on all patients who have been diagnosed with COVID-19 in the province of Tehran from March 2020 up to Dec 2020 was conducted. Data on socio-demographic characteristics, clinical presentations, comorbidities, and the health outcomes of 205,654 patients were examined. Characteristics of the study population were described. To assess the association of study variables with the disease severity, the Chi-Squared test and Multiple Logistic Regression model were applied. RESULTS: The mean age of the study population was 52.8 years and 93,612 (45.5%) were women. About half of the patients have presented with low levels of blood oxygen saturation. The ICU admission rate was 17.8% and the overall mortality rate was 10.0%. Older age, male sex, comorbidities including hypertension, cancer, chronic respiratory diseases other than asthma, chronic liver diseases, chronic kidney diseases, chronic neurological disorders, and HIV/AIDS infection were risk markers of poor health outcome. Clinical presentations related with worse prognosis included fever, difficulty breathing, impaired consciousness, and cutaneous manifestations. CONCLUSION: These results might alert physicians to pay attention to determinants and risk factors associated with poor prognosis in patients with COVID-19. In addition, our findings aid decision makers to emphasise on vulnerable groups in the public health strategies that aim at preventing the spread of the disease and its mortalities.

Mechanisms of Sound-Induced Opening of the Blood-Brain Barrier.

The blood-brain barrier (BBB) poses a significant challenge for drug delivery to the brain. The limitations of our knowledge about the nature of BBB explain the slow progress in the therapy of brain diseases and absence of methods for drug delivery to the brain in clinical practice. Here, we show that the BBB opens for high-molecular-weight compounds after exposure to loud sound (100 dB 370 Hz) in rats. The role of stress induced by loud sound and the systemic and molecular mechanisms behind it are discussed in the framework of the BBB. This opens an informative platform for novel fundamental knowledge about the nature of BBB and for the development of a noninvasive brain drug delivery technology.

Transcranial Photobiomodulation of Clearance of Beta-Amyloid from the Mouse Brain: Effects on the Meningeal Lymphatic Drainage and Blood Oxygen Saturation of the Brain.

Here, we demonstrate the therapeutic effects of transcranial photobiomodulation (tPBM, 1267 nm, 32 J/cm2, a 9-day course) in mice with the injected model of Alzheimer's disease (AD) associated with accumulation of beta-amyloid (Aß) in the brain resulting in neurocognitive deficit vs. the control group (CG) (the neurological severity score (NNS), AD 3.67 ± 0.58 vs. CG 1.00 ± 0.26%, p < 0.05) and mild cerebral hypoxia (AD 72 ± 6% vs. CG 97 ± 2%, p < 0.001). The course of tPBM improved neurocognitive status of mice with AD (NNS, AD 2.03 ± 0.14 vs. CG 1.00 ± 0.26, vs. 2.03 ± 0.14, p < 0.05) due to stimulation of clearance of Aß from the brain via the meningeal lymphatic vessels (the immunohistochemical and confocal data) and an increase in blood oxygen saturation of the brain tissues (the pulse oximetry data) till 85 ± 2%, p < 0.05. These results open breakthrough strategies for non-pharmacological therapy of AD and clearly demonstrate that tPBM might be a promising therapeutic target for preventing or delaying AD based on stimulation of oxygenation of the brain tissues and activation of clearance of toxic molecules via the cerebral lymphatics.

Photoplethysmography behind the Ear Outperforms Electrocardiogram for Cardiovascular Monitoring in Dynamic Environments.

An increasing proportion of occupational mishaps in dynamic, high-risk operational environments have been attributed to human error, yet there are currently no devices to routinely provide accurate physiological data for insights into underlying contributing factors. This is most commonly due to limitations of commercial and clinical devices for collecting physiological data in environments of high motion. Herein, a novel Photoplethysmography (PPG) sensor device was tested, called SPYDR (Standalone Performance Yielding Deliberate Risk), reading from a behind-the-ear location, specifically designed for high-fidelity data collection in highly dynamic high-motion, high-pressure, low-oxygen, and high-G-force environments. For this study, SPYDR was installed as a functional ear-cup replacement in flight helmets worn by rated US Navy aircrew. Subjects were exposed to reduced atmospheric pressure using a hypobaric chamber to simulated altitudes of 25,000 feet and high G-forces in a human-rated centrifuge up to 9 G acceleration. Data were compared to control devices, finger and forehead PPG sensors, and a chest-mounted 12-lead ECG. SPYDR produced high-fidelity data compared to controls with little motion-artifact controls in the no-motion environment of the hypobaric chamber. However, in the high-motion, high-force environment of the centrifuge, SPYDR recorded consistent, accurate data, whereas PPG controls and ECG data were unusable due to a high-degree-motion artifacts. The data demonstrate that SPYDR provides an accurate and reliable system for continuous physiological monitoring in high-motion, high-risk environments, yielding a novel method for collecting low-artifact cardiovascular assessment data important for investigating currently inaccessible parameters of human physiology.

Design Implementation and Evaluation of a Mobile Continuous Blood Oxygen Saturation Monitoring System.

OBJECTIVE: In this study, we built a mobile continuous Blood Oxygen Saturation (SpO2) monitor, and for the first time, explored key design principles towards daily applications. METHODS: We firstly built a customized wearable computer that can sense two-channel photoplethysmogram (PPG) signals, and transmit the signals wirelessly to smartphone. Afterwards, we explored many SpO2 model building principles, focusing on linear/nonlinear models, different PPG parameter calculation methods, and different finger types. Moreover, we further compared PPG sensor placement principles by comparing different hand configurations and different finger configurations. Finally, a dataset collected from eleven human subjects was used to evaluate the mobile health monitor and explore all of the above design principles. RESULTS: The experimental results show that the root mean square error of the SpO2 estimation is only 1.8, indicating the effectiveness of the system. CONCLUSION: These results indicate the effectiveness of the customized mobile SpO2 monitor and the selected design principles. SIGNIFICANCE: This research is expected to facilitate the continuous SpO2 monitoring of patients with clinical indications.

[Relationship between sleep architecture and severity of obstructive sleep apnea].

OBJECTIVE: To investigate the effect of obstructive sleep apnea (OSA) on different sleep stages, and the relationship between N3 stage of non-rapid eye movement sleep and respiratory abnormal events. METHODS: A total of 188 adult patients who underwent overnight polysomnography(PSG)monitoring in Sir Run Run shaw Hospital of Zhejiang University from June 24th to December 26th 2019 were enrolled in the study. OSA patients were classified into 3 groups (mild, moderate and severe) according to the apnea-hypopnea index (AHI). PSG data, AHI and the lowest SPO2 in each stage of sleep were compared among three groups. RESULTS: There was no significant difference in total sleep time and sleep efficiency among patients with different severity of OSA (all P>0.05). The proportion of N3 stage in moderate and severe OSA groups were significantly smaller than that in mild OSA group (all P<0.05). The proportion of N3 stage in severe OSA group was also smaller than that in moderate OSA group (P<0.05). In addition, severe OSA group had a longer latency of N3 stage than mild and moderate OSA groups (all P<0.05). The latency of N3 stage in moderate OSA group was longer than that in mild OSA group (P<0.05). The AHI in N3 stage was markedly lower than that in other sleep stages (all P<0.01), regardless of the severity of OSA. Supine AHI in N3 stage in mild and moderate groups was significantly lower than that in N1, N2 and rapid eye movement (REM) stages (all P<0.01). Supine AHI in N3 stage in severe group was also lower than that in N2 and REM stages (P<0.05 or P<0.01). The lowest SPO2 in N3 stage was significantly higher than that in N1, N2 and REM stages (P<0.05 or P<0.01), regardless of the severity of OSA. CONCLUSIONS: s The proportion of N3 stage is lower in OSA patients, and N3 stage has less sleep respiratory events than non-N3 stages. The results suggest that the increased N3 stage proportion may indicate less severity of OSA.

Mapping hepatic blood oxygenation by quantitative BOLD (qBOLD) MRI.

PURPOSE: Abnormalities in hepatic oxygen delivery and oxygen consumption may serve as a significant indicator of hepatic cellular dysfunction and may predict treatment response. However, conventional and oxygen-enhanced hepatic BOLD MRI can only provide semiquantitative assessment of hepatic oxygenation. METHODS: A hepatic quantitative BOLD (qBOLD) model was proposed for noninvasive mapping of hepatic venous blood oxygen saturation (Yv ) and deoxygenated blood volume (DBV) in human subjects. The validity and the estimation bias of the proposed model were evaluated by Monte Carlo simulations. Eight healthy subjects were scanned after written consent with institutional review board approval. RESULTS: Monte Carlo simulations demonstrated that the proposed single-compartment hepatic qBOLD model leads to significant deviation of the predicted T2* decay profile from the simulated signal due to high hepatic blood volume fraction. Small relative estimation bias for hepatic Yv and significant overestimation for hepatic DBV were observed, which can be corrected by applying the calibration curves established from simulations. After correction, the mean hepatic Yv in human subjects was 56.8 ± 6.8%, and the mean hepatic DBV was 0.190 ± 0.035, consistent with measurements from other invasive approaches. Except in regions with significant vascular contamination, the maps for hepatic Yv and DBV were relatively homogenous. CONCLUSIONS: With estimation bias correction, the hepatic qBOLD approach enables noninvasive mapping of hepatic blood volume and oxygenation in human subjects. The established protocol may be used to quantitatively assess hepatic tissue hypoxia in multiple liver diseases.

[Development of a Portable Pulse Oxymetry Simulator System].

This article describes the design of a portable blood oxygen simulation system that can be used to simulate various blood gas saturation states of the human body. The system can be used to simulate various states of blood gas saturation, and can also simulate large blood oxygen saturation dynamic range, pulse rate range and perfusion index range. It can be used for testing, but not for clinical examination instruments. Moreover, the system has the characteristics of small size and low cost compared with the commercial blood oxygen simulator. Although the simulation system is not directly used for the detection of blood gas saturation of patients, it is also an essential equipment in the production and testing process, so it has certain practical value.