Measurement Of Blood Oxygen Saturation Research Articles

The Development and Implementation of Innovative Blind Source Separation Techniques for Real-Time Extraction and Analysis of Fetal and Maternal Electrocardiogram Signals.

This article presents an innovative approach to analyzing and extracting electrocardiogram (ECG) signals from the abdomen and thorax of pregnant women, with the primary goal of isolating fetal ECG (fECG) and maternal ECG (mECG) signals. To resolve the difficulties related to the low amplitude of the fECG, various noise sources during signal acquisition, and the overlapping of R waves, we developed a new method for extracting ECG signals using blind source separation techniques. This method is based on independent component analysis algorithms to detect and accurately extract fECG and mECG signals from abdomen and thorax data. To validate our approach, we carried out experiments using a real and reliable database for the evaluation of fECG extraction algorithms. Moreover, to demonstrate real-time applicability, we implemented our method in an embedded card linked to electronic modules that measure blood oxygen saturation (SpO2) and body temperature, as well as the transmission of data to a web server. This enables us to present all information related to the fetus and its mother in a mobile application to assist doctors in diagnosing the fetus's condition. Our results demonstrate the effectiveness of our approach in isolating fECG and mECG signals under difficult conditions and also calculating different heart rates (fBPM and mBPM), which offers promising prospects for improving fetal monitoring and maternal healthcare during pregnancy.

Tissue mimicking materials and finger phantom design for pulse oximetry.

Pulse oximetry represents a ubiquitous clinical application of optics in modern medicine. Recent studies have raised concerns regarding the potential impact of confounders, such as variable skin pigmentation and perfusion, on blood oxygen saturation measurement accuracy in pulse oximeters. Tissue-mimicking phantom testing offers a low-cost, well-controlled solution for characterizing device performance and studying potential error sources, which may thus reduce the need for costly in vivo trials. The purpose of this study was to develop realistic phantom-based test methods for pulse oximetry. Material optical and mechanical properties were reviewed, selected, and tuned for optimal biological relevance, e.g., oxygenated tissue absorption and scattering, strength, elasticity, hardness, and other parameters representing the human finger's geometry and composition, such as blood vessel size and distribution, and perfusion. Relevant anatomical and physiological properties are summarized and implemented toward the creation of a preliminary finger phantom. To create a preliminary finger phantom, we synthesized a high-compliance silicone matrix with scatterers for embedding flexible tubing and investigated the addition of these scatterers to novel 3D printing resins for optical property control without altering mechanical stability, streamlining the production of phantoms with biologically relevant characteristics. Phantom utility was demonstrated by applying dynamic, pressure waveforms to produce tube volume change and resultant photoplethysmography (PPG) signals. 3D printed phantoms achieved more biologically relevant conditions compared to molded phantoms. These preliminary results indicate that the phantoms show strong potential to be developed into tools for evaluating pulse oximetry performance. Gaps, recommendations, and strategies are presented for continued phantom development.

A retrospective cohort study on early antibiotic use in vaccinated and unvaccinated COVID-19 patients.

The bacteriophage behavior of SARS-CoV-2 during the acute and post-COVID-19 phases appears to be an important factor in the development of the disease. The early use of antibiotics seems to be crucial to inhibit disease progression-to prevent viral replication in the gut microbiome, and control toxicological production from the human microbiome. To study the impact of specific antibiotics on recovery from COVID-19 and long COVID (LC) taking into account: vaccination status, comorbidities, SARS-CoV-2 wave, time of initiation of antibiotic therapy and concomitant use of corticosteroids and nonsteroidal anti-inflammatory drugs (NSAIDs). A total of 211 COVID-19 patients were included in the study: of which 59 were vaccinated with mRNA vaccines against SARS-CoV-2 while 152 were unvaccinated. Patients were enrolled in three waves: from September 2020 to October 2022, corresponding to the emergence of the pre-Delta, Delta, and Omicron variants of the SARS-CoV-2 virus. The three criteria for enrolling patients were: oropharyngeal swab positivity or fecal findings; moderate symptoms with antibiotic intake; and measurement of blood oxygen saturation during the period of illness. The use of antibiotic combinations, such as amoxicillin with clavulanic acid (875 + 125 mg tablets, every 12 h) plus rifaximin (400 mg tablets every 12 h), as first choice, as suggested from the previous data, or azithromycin (500 mg tablets every 24 h), plus rifaximin as above, allows healthcare professionals to focus on the gut microbiome and its implications in COVID-19 disease during patient care. The primary outcome measured in this study was the estimated average treatment effect, which quantified the difference in mean recovery between patients receiving antibiotics and those not receiving antibiotics at 3 and 9 days after the start of treatment. In the analysis, both vaccinated and unvaccinated groups had a median illness duration of 7 days (interquartile range [IQR] 6-9 days for each; recovery crude hazard ratio [HR] = 0.94, p = 0.700). The median illness duration for the pre-Delta and Delta waves was 8 days (IQR 7-10 days), while it was shorter, 6.5 days, for Omicron (IQR 6-8 days; recovery crude HR = 1.71, p < 0.001). These results were confirmed by multivariate analysis. Patients with comorbidities had a significantly longer disease duration: median 8 days (IQR 7-10 days) compared to 7 days (IQR 6-8 days) for those without comorbidities (crude HR = 0.75, p = 0.038), but this result was not confirmed in multivariate analysis as statistical significance was lost. Early initiation of antibiotic therapy resulted in a significantly shorter recovery time (crude HR = 4.74, p < 0.001). Concomitant use of NSAIDs did not reduce disease duration and in multivariate analysis prolonged the disease (p = 0.041). A subgroup of 42 patients receiving corticosteroids for a median of 3 days (IQR 3-6 days) had a longer recovery time (median 9 days, IQR 8-10 days) compared to others (median 7 days, IQR 6-8 days; crude HR = 0.542, p < 0.001), as confirmed also by the adjusted HR. In this study, a statistically significant reduction in recovery time was observed among patients who received early antibiotic treatment. Early initiation of antibiotics played a crucial role in maintaining higher levels of blood oxygen saturation. In addition, it is worth noting that a significant number of patients who received antibiotics in the first 3 days and for a duration of 7 days, during the acute phase did not develop LC.

Reliability of continuous vital sign monitoring in post-operative patients employing consumer-grade fitness trackers: A randomised pilot trial.

Fitness trackers can provide continuous monitoring of vital signs and thus have the potential to become a complementary, mobile and effective tool for early detection of patient deterioration and post-operative complications. To evaluate potential implementations in acute care setting, we included 36 patients after moderate to major surgery in a recent randomised pilot trial to compare the performance of vital sign monitoring by three different fitness trackers (Apple Watch 7, Garmin Fenix 6pro and Withings ScanWatch) with established standard clinical monitors in post-anaesthesia care units and monitoring wards. During a cumulative period of 56 days, a total of 53,197 heart rate (HR) measurements, as well as 12,219 measurements of the peripheral blood oxygen saturation (SpO2) and 28,954 respiratory rate (RR) measurements were collected by fitness trackers. Under real-world conditions, HR monitoring was accurate and reliable across all benchmarked devices (r = [0.95;0.98], p < 0.001; Bias = [-0.74 bpm;-0.01 bpm]; MAPE∼2%). However, the performance of SpO2 (r = [0.21;0.68]; p < 0.001; Bias = [-0.46%;-2.29%]; root-mean-square error = [2.82%;4.1%]) monitoring was substantially inferior. RR measurements could not be obtained for two of the devices, therefore exclusively the accuracy of the Garmin tracker could be evaluated (r = 0.28, p < 0.001; Bias = -1.46/min). Moreover, the time resolution of the vital sign measurements highly depends on the tracking device, ranging from 0.7 to 117.94 data points per hour. According to the results of the present study, tracker devices are generally reliable and accurate for HR monitoring, whereas SpO2 and RR measurements should be interpreted carefully, considering the clinical context of the respective patients.

Acceptance of the Apple Watch Series 6 for Telemonitoring of Older Adults With Chronic Obstructive Pulmonary Disease: Qualitative Descriptive Study Part 1.

The Apple Watch is not a medical device per se; it is a smart wearable device that is increasingly being used for health monitoring. Evidence exists that the Apple Watch Series 6 can reliably measure blood oxygen saturation (SpO2) in patients with chronic obstructive pulmonary disease under controlled circumstances. This study aimed to better understand older adults' acceptance of the Watch as a part of telemonitoring, even with these advancements. This study conducted content analysis on data collected from 10 older adults with chronic obstructive pulmonary disease who consented to wear the Watch. Using the Extended Unified Theory of Acceptance and Use of Technology model, results showed that participants experienced potential health benefits; however, the inability of the Watch to reliably measure SpO2 when in respiratory distress was concerning. Participants' level of tech savviness varied, which caused some fear and frustration at the start, yet all felt supported by family and would have explored more features if they owned the Watch. All agreed that the Watch is mainly a medical tool and not a gadget. To conclude, although the Watch may enhance their physical health and well-being, results indicated that participants are more likely to accept the Watch if it ultimately proves to be useful when experiencing respiratory distress.

Enhanced SpO2 estimation using explainable machine learning and neck photoplethysmography

Reflectance-based photoplethysmogram (PPG) sensors provide flexible options of measuring sites for blood oxygen saturation (SpO2) measurement. But they are mostly limited by accuracy, especially when applied to different subjects, due to the diverse human characteristics (skin colors, hair density, etc.) and usage conditions of different sensor settings. This study addresses the estimation of SpO2 at non-standard measuring sites employing reflectance-based sensors. It proposes an automated construction of subject inclusion-exclusion criteria for SpO2 measuring devices, using a combination of unsupervised clustering, supervised regression, and model explanations. This is perhaps among the first adaptation of SHAP to explain the clusters gleaned from unsupervised learning methods. As a wellness application case study, we developed a pillow-based wearable device to collect reflectance PPGs from both the brachiocephalic and carotid arteries around the neck. The experiment was conducted on 33 subjects, each under totally 80 different sensor settings. The proposed approach addressed the variations of humans and devices, as well as the heterogeneous mapping between signals and SpO2 values. It identified effective device settings and characteristics of their applicable subject groups (i.e., subject inclusion-exclusion criteria). Overall, it reduced the root mean squared error (RMSE) by 16%, compared to an empirical formula and a plain SpO2 estimation model.

Evaluating blood oxygen saturation measurements by popular fitness trackers in postoperative patients: A prospective clinical trial

Blood oxygen saturation is an important clinical parameter, especially in postoperative hospitalized patients, monitored in clinical practice by arterial blood gas (ABG) and/or pulse oximetry that both are not suitable for a long-term continuous monitoring of patients during the entire hospital stay, or beyond. Technological advances developed recently for consumer-grade fitness trackers could-at least in theory-help to fill in this gap, but benchmarks on the applicability and accuracy of these technologies in hospitalized patients are currently lacking. We therefore conducted at the postanaesthesia care unit under controlled settings a prospective clinical trial with 201 patients, comparing in total >1,000 oxygen blood saturation measurements by fitness trackers of three brands with the ABG gold standard and with pulse oximetry. Our results suggest that, despite of an overall still tolerable measuring accuracy, comparatively high dropout rates severely limit the possibilities of employing fitness trackers, particularly during the immediate postoperative period of hospitalized patients.

RANCANG BANGUN ALAT PENDETEKSI GOLONGAN DARAH DAN SATURASI OKSIGEN BERBASIS ARDUINO UNO

In this study a device was designed to detect human blood group using the ABO method which is integrated with a blood oxygen saturation meter. This tool can detect agglutination or non-agglutination reactions in blood samples that have been treated with antisera and will then be read by three TCRT5000 sensors which are reflective sensors used as detectors of A, B and Rhesus antigens when agglutination and non-agglutination reactions occur on paper. blood sample test. In addition, the MAX30100 sensor is also used to measure blood oxygen saturation in the human body. Data that has been read by the sensor will be directly processed by Arduino Uno and the results from reading by the sensor will be displayed on the 16x2 LCD. In testing the human blood group detector designed where the results of all tests on the respondent's blood samples totaling 8 blood samples obtained a success value of 100%. In addition, the results of testing the Oxygen Saturation Measuring Instrument using the MAX30100 sensor obtained an accuracy value of 99.53%.

The Effects of the Myobrace® System on Peripheral Blood Oxygen Saturation (SpO2) in Patients with Mixed Dentition with Oral Dysfunction.

Myobrace® is an orthodontic device that has the purpose of correcting oral dysfunctions, thus predisposing the physiological growth of the jaws, aligning teeth, and optimizing face development. This device is usually associated with Myobrace® Activities to reach this target. Considering the lack of studies in the literature about peripheral blood oxygen saturation (SpO2) and the use of preformed oral devices, the aim of this study is to quantify the change in blood oxygen saturation (SpO2) in patients treated with the Myobrace® System in mixed dentition. In this study, 23 children (11 females and 12 males) were involved, who were affected by different oral dysfunctions and were treated with a Myobrace®. Blood oxygen saturation measurements were taken at baseline and after every four months for a year. The SpO2 measurements were taken in the rest position and with a closed mouth for a total of 12 min-6 min with and 6 min without the Myobrace® oral device. All data points were anonymized and recorded on an Excel spreadsheet. A statistical analysis was carried out. Therapy with a Myobrace® in patients with mixed dentition resulted in a statistically significant increase in oxygen saturation. In particular, in patients with a closed mouth, a statistically significant increase in oxygen saturation was observed, bringing it from 97.66% to 99.00%, while in the rest position, the increase was from 98.03% to 99.07%. The use of Myobrace® devices in patients with mixed dentition could lead to a significant improvement in blood oxygen saturation.

Non-invasive arterial blood pressure measurement and SpO2 estimation using PPG signal: a deep learning framework

BackgroundMonitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measurement methods have intrinsic limitations; for instance, arterial blood pressure is measured by inserting a catheter in the artery causing discomfort and infection.MethodPhotoplethysmogram (PPG) signals can be collected via non-invasive devices, and therefore have stimulated researchers’ interest in exploring blood pressure estimation using machine learning and PPG signals as a non-invasive alternative. In this paper, we propose a Transformer-based deep learning architecture that utilizes PPG signals to conduct a personalized estimation of arterial systolic blood pressure, arterial diastolic blood pressure, and oxygen saturation.ResultsThe proposed method was evaluated with a subset of 1,732 subjects from the publicly available ICU dataset MIMIC III. The mean absolute error is 2.52 ± 2.43 mmHg for systolic blood pressure, 1.37 ± 1.89 mmHg for diastolic blood pressure, and 0.58 ± 0.79% for oxygen saturation, which satisfies the requirements of the Association of Advancement of Medical Instrumentation standard and achieve grades A for the British Hypertension Society standard.ConclusionsThe results indicate that our model meets clinical standards and could potentially boost the accuracy of blood pressure and oxygen saturation measurement to deliver high-quality healthcare.

Investigating the accuracy of blood oxygen saturation measurements in common consumer smartwatches.

Blood oxygen saturation (SpO2) is an important measurement for monitoring patients with acute and chronic conditions that are associated with low blood oxygen levels. While smartwatches may provide a new method for continuous and unobtrusive SpO2 monitoring, it is necessary to understand their accuracy and limitations to ensure that they are used in a fit-for-purpose manner. To determine whether the accuracy of and ability to take SpO2 measurements from consumer smartwatches is different by device type and/or by skin tone, our study recruited patients aged 18-85 years old, with and without chronic pulmonary disease, who were able to provide informed consent. The mean absolute error (MAE), mean directional error (MDE) and root mean squared error (RMSE) were used to evaluate the accuracy of the smartwatches as compared to a clinical grade pulse oximeter. The percent of data unobtainable due to inability of the smartwatch to record SpO2 (missingness) was used to evaluate the measurability of SpO2 from the smartwatches. Skin tones were quantified based on the Fitzpatrick (FP) scale and Individual Typology Angle (ITA), a continuous measure of skin tone. A total of 49 individuals (18 female) were enrolled and completed the study. Using a clinical-grade pulse oximeter as the reference standard, there were statistically significant differences in accuracy between devices, with Apple Watch Series 7 having measurements closest to the reference standard (MAE = 2.2%, MDE = -0.4%, RMSE = 2.9%) and the Garmin Venu 2s having measurements farthest from the reference standard (MAE = 5.8%, MDE = 5.5%, RMSE = 6.7%). There were also significant differences in measurability across devices, with the highest data presence from the Apple Watch Series 7 (88.9% of attempted measurements were successful) and the highest data missingness from the Withings ScanWatch (only 69.5% of attempted measurements were successful). The MAE, RMSE and missingness did not vary significantly across FP skin tone groups, however, there may be a relationship between FP skin tone and MDE (intercept = 0.04, beta coefficient = 0.47, p = 0.04). No statistically significant difference was found between skin tone as measured by ITA and MAE, MDE, RMSE or missingness.

Design of Basic Vital Signs Measurement Tool And Dehydration Early Detection in Human Body

A tool has been made to monitor vital signs such as heart rate, oxygen saturation in the blood, and body temperature based on a microcontroller which is based on dehydration conditions where the body loses more fluid than the amount of fluid it enters. Parameters for carrying out this detection include heart rate, blood oxygen saturation (SpO2), body temperature and urine color. The targets of this research are (a) making a prototype, (b) programming the system with the help of the Arduino IDE, and (c) measuring system performance. The research method starts from making a prototype and measuring system performance. The results of measuring the performance of the tool show that the error for measuring heart rate is 1.28%, measuring blood oxygen saturation (SpO2) is 0.51%, and measuring body temperature is 1.729%. However, for the dehydration detection test from 5 test samples, the results showed a success percentage of 60% with an average error of 40%. Overall the tool can function well

Feasibility of using intermittent active monitoring of vital signs by smartphone users to predict SARS-CoV-2 PCR positivity

Early detection of highly infectious respiratory diseases, such as COVID-19, can help curb their transmission. Consequently, there is demand for easy-to-use population-based screening tools, such as mobile health applications. Here, we describe a proof-of-concept development of a machine learning classifier for the prediction of a symptomatic respiratory disease, such as COVID-19, using smartphone-collected vital sign measurements. The Fenland App study followed 2199 UK participants that provided measurements of blood oxygen saturation, body temperature, and resting heart rate. Total of 77 positive and 6339 negative SARS-CoV-2 PCR tests were recorded. An optimal classifier to identify these positive cases was selected using an automated hyperparameter optimisation. The optimised model achieved an ROC AUC of 0.695 ± 0.045. The data collection window for determining each participant’s vital sign baseline was increased from 4 to 8 or 12 weeks with no significant difference in model performance (F(2) = 0.80, p = 0.472). We demonstrate that 4 weeks of intermittently collected vital sign measurements could be used to predict SARS-CoV-2 PCR positivity, with applicability to other diseases causing similar vital sign changes. This is the first example of an accessible, smartphone-based remote monitoring tool deployable in a public health setting to screen for potential infections.

1400-P: Low Blood Oxygen Saturation Is Associated with Impaired Glucose Control in Diabetes

Low Blood Oxygen Saturation (BOS) is associated with increased overall morbidity / mortality and prevalence of diabetes is known to increase with altitude (lower 02 partial pressure). Individuals with complicated diabetes commonly have low blood oxygen saturation compared with nondiabetic patients. To unravel the link between low BOS and glucose metabolism, we investigated the correlation between BOS and glucose, BOS and HbA1c levels, BOS and VO2 consumption (Resting Energy Expenditure) in a cohort of adults with diabetes mellitus. The study included 1362 adults with diabetes (616 F, 746 M; 66.4 ± 14.2 years, range 18-85 years; BMI 27.6 ± 5.0 kg/m2, range 18-49.6 kg/m2; SpO2 97.2 ± 1.4%, range 88-100%; glucose 137.7 ± 45.0 mg/dl, range 50.0-323.0 mg/dl). A significant inverse correlation (Pearson) between the glucose (glucometer) and the BOS (pulsoximeter) (p&amp;lt;0.0001*; r = -0.1530). An inverse correlation (Pearson correlation) between the HbA1c levels and the BOS (n=1295; 568 F, 727 M; 67.5 ± 13.1 years, range 18-85 years; BMI 27.8 ± 5.2 kg/m2, range 18-49.8 kg/m2; HbA1c 52.9 ± 13.0, range 25-152 mmol/mol; p&amp;lt;0.0001*; r = -0.1351). In summary, we showed an inverse relationship between oxygen saturation and both glucose and glycosylated hemoglobin levels. Although the exact mechanisms behind lower blood oxygen saturation in diabetes are unknown, we speculate that a reduced pulmonary diffusion capacity as a consequence of pulmonary microvascular damage could play an important role. In conclusion, present preliminary data indicate the routine measurement of BOS along with glucose and glycosylated hemoglobin in the outpatient visit setting of diabetic patients as a biomarker of seriousness of disease. Disclosure L. Luzi: Speaker's Bureau; A. Menarini Diagnostics, Amgen Inc., Boehringer Ingelheim and Eli Lilly Alliance. Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Research Support; Gelesis. Advisory Panel; Medtronic. Speaker's Bureau; Novo Nordisk, Novartis. C. Macrì: None. A. Ferrulli: None. C.C. Berra: None. C. Romano: None. S. Massarini: None. Funding IRCCS MultiMedica (Ricerca Corrente)

Efforts toward the continuous monitoring of molecular markers of performance.

Technologies supporting the continuous, real-time measurement of blood oxygen saturation and plasma glucose levels have improved our ability to monitor performance status. Our ability to monitor other molecular markers of performance, however, including the hormones known to indicate overtraining and general health, has lagged. That is, although a number of other molecular markers of performance status have been identified, we have struggled to develop viable technologies supporting their real-time monitoring in the body. Here we review biosensor approaches that may support such measurements, as well as the molecules potentially of greatest interest to monitor. Narrative literature review. Literature review. Significant effort has been made to harness the specificity, affinity, and generalizability of biomolecular recognition in a platform technology supporting continuous in vivo molecular measurements. Most biosensor approaches, however, are either not generalizable to most targets, or fail when challenged in the complex environments found in vivo. Electrochemical aptamer-based sensors, in contrast, are the first technology to simultaneously achieve both of these critical attributes. In an effort to illustrate the potential of this platform technology, we both critically review the literature describing it and briefly survey some of the molecular performance markers we believe will prove advantageous to monitor using it. Electrochemical aptamer-based sensors may be the first truly generalizable technology for monitoring specific molecules in situ in the body and how adaptation of the platform to subcutaneous microneedles will enable the real-time monitoring of performance markers via a wearable, minimally invasive device.

Novel Energy Drink Improves Cognitive Function and Mood, without Influencing Myocardial Oxygen Demand or Ventricular Repolarization in Adult Gamers: A Randomized, Double-Blind, Placebo-Controlled, Crossover Trial

There are limited available data assessing the efficacy of acute energy drink consumption on cognition and gaming performance, nor on cardiovascular safety. Objectives To examine the efficacy of acute consumption of a novel energy drink (C4S) versus placebo for improving cognitive and gaming performance and mood. Secondarily, we examined the cardiovascular safety profile of acute C4S consumption. Methods Forty-five healthy, young adult video gamers completed two experimental visits in randomized order where they consumed either C4S or a placebo and then completed a validated battery of neurocognitive tests, played five video games, and completed a mood state survey. Blood pressure (BP), heart rate (HR), oxygen saturation, and electrocardiogram measurements were taken at baseline and repeated throughout each visit. Results Acute consumption of C4S improved cognitive flexibility (absolute mean or median difference [95% CI] = +4.3 [2.2–6.4]; p < 0.001; d = 0.63), executive function (+4.3 [2.3–6.3]; p < 0.001; d = 0.63), sustained attention (+2.1 [0.6–3.6]; p = 0.01; d = 0.44), motor speed (+2.9 [0.8–4.9]; p < 0.001; d = 0.44), psychomotor speed (+3.9 [0.1–7.7]; p = 0.04; d = 0.32) working memory (+1.0 [0.1–1.9]; p = 0.02; d = 0.35), and performance in the two-dimensional visuospatial game Tetris (+463 [-419–2,065] pts; p = 0.049; d = 0.30) compared to placebo. C4S also improved Fatigue-Inertia (-1 [-3–0]; p = 0.004; d = 0.45), Vigor-Activity (+2.4 [1.3–3.6]; p < 0.001; d = 0.64), Friendliness (+0 [0–1]; p = 0.04; d = 0.32), and Total Mood Disturbance (-3 [-6–0]; p = 0.002; d = 0.44). BP increased slightly in C4S versus placebo, while HR decreased from baseline to post-drink in the C4S condition. Rate-pressure-product was higher in C4S versus placebo independent of time but did not increase from baseline. There was no effect on corrected QT interval. Conclusion Acute consumption of C4S was efficacious for cognitive performance, visuospatial gaming performance, and mood enhancement, and had no effect on myocardial oxygen demand or ventricular repolarization, despite being associated with increases in BP.

Pulse Oximetry Imaging System Using Spatially Uniform Dual Wavelength Illumination.

Pulse oximetry is a non-invasive method for measuring blood oxygen saturation. However, its detection scheme heavily relies on single-point measurements. If the oxygen saturation is measured at a single location, the measurements are influenced by the profile of illumination, spatial variations in blood flow, and skin pigment. To overcome these issues, imaging systems that measure the distribution of oxygen saturation have been demonstrated. However, previous imaging systems have relied on red and near-infrared illuminations with different profiles, resulting in inconsistent ratios between transmitted red and near-infrared light over space. Such inconsistent ratios can introduce fundamental errors when calculating the spatial distribution of oxygen saturation. In this study, we developed a novel illumination system specifically designed for a pulse oximetry imaging system. For the illumination system, we customized the integrating sphere by coating a mixture of barium sulfate and white paint inside it and by coupling eight red and eight near-infrared LEDs. The illumination system created identical patterns of red and near-infrared illuminations that were spatially uniform. This allowed the ratio between transmitted red and near-infrared light to be consistent over space, enabling the calculation of the spatial distribution of oxygen saturation. We believe our developed pulse oximetry imaging system can be used to obtain spatial information on blood oxygen saturation that provides insight into the oxygenation of the blood contained within the peripheral region of the tissue.

Motor Vehicle Driver Monitoring System to Prevent Traffic Accident

Traffic accident data shows an upward trend. One of the contributing factors is the condition of the driver who is tired or sleepy due to decreased oxygen saturation in the blood (SpO2). If the oxygen saturation in the blood (SpO2) decreases, the oxygen supply to the brain also decreases, which causes the driver to feel tired or sleepy, even to shortness of breath. By using a pulse oximeter sensor mounted on the wrist, oxygen saturation in the blood (SpO2) can be detected. The results of the sensor readings are then sent using blue tooth technology to the microcontroller and displayed on the monitor. If the driver is tired or sleepy, there will be a warning that the driver should take a rest immediately. Based on the results of trials that have been carried out, the average error in measuring blood oxygen saturation (SpO2) is 0.52%.

PPG Signal and application in the medical field

The ascent of remote health examination is a burgeoning trend in healthcare, aimed at tackling the challenge of hospital overload and streamlining the process of patient monitoring. To achieve these laudable goals, a device that is both efficient and capable of extracting critical health indicators is of paramount importance. Enter photoplethysmography (PPG) technology - a compact and user-friendly device that offers a wealth of health-related information. PPG is an optical, non-invasive method of measuring changes in blood volume in tissue by illuminating the skin and detecting variations in light absorption caused by blood flow. This technique has a multitude of applications, including the measurement of blood oxygen saturation, the estimation of blood pressure, the assessment of vascular aging, and the detection of arrhythmias. Therefore, it presents a promising avenue in addressing the challenge of hospital overload. This article provides an all-encompassing overview of photoplethysmography (PPG) technology, elucidating the underlying principles and highlighting its noteworthy applications. Specifically, the article expounds on the use of PPG in measuring blood oxygen saturation, estimating blood pressure, assessing vascular aging, and detecting arrhythmias. Despite the advantageous applications of PPG, there are still some issues that need to be addressed, such as the limited availability of PPG data sets in certain populations, the sensitivity of PPG signal to motion and ambient conditions, and a lack of clarity about the nature of PPG which leads to the absence of standard criteria in sampling and interpretation of PPG in its applications. And these issues are also thoroughly discussed in the paper.

Design and Implementation of a Healthcare Monitoring System Based on LoRa

For humans to survive, scientific and technological advancements must be able to contribute to the solution of human medical issues. The design and implementation of a monitoring system for the measurement of blood oxygen saturation, heart rate, and body temperature have been combined into one tool in this study. The measurement results are shown both on the measuring instrument's OLED display and a remote monitoring system's LCD display. This instrument uses ESP32 as a Microcontroller and LoRa as a wireless communication technique. The MLX90614 sensor is used to detect body temperature, while the MAX30100 sensor is used to monitor blood oxygen saturation and heart rate. Testing Measurements are calibrated using instruments that meet industrial standards (Wincom infrared thermometer and GE patient monitor) used in the hospital. When compared to industry-standard instruments, the tool's accuracy is 98.18% for measurements of blood oxygen saturation, 96.54 % for measurements of heart rate, and 98.78 % for measurements of body temperature. The instrument's total accuracy, calculated as the average of all three factors, was 97.63 %. If the abnormalities in the recorded parameters are detected, then an alert will be triggered (buzzer and blinking LED). this instrument can help the patients to check their health status and provide remote monitoring of health providers.