Non-Contact SpO2 Prediction System Based on a Digital Camera

Preserving privacy and video quality through remote physiological signal removal

The revolutionary remote photoplethysmography (rPPG) technique has enabled intelligent devices to estimate physiological parameters with remarkable accuracy. However, the continuous and surreptitious recording of individuals by these devices and the collecting of sensitive health data without users' knowledge or consent raise serious privacy concerns. Here we explore frugal methods for modifying facial videos to conceal physiological signals while maintaining image quality. Eleven lightweight modification methods, including blurring operations, additive noises, and time-averaging techniques, were evaluated using five different rPPG techniques across four activities: rest, talking, head rotation, and gym. These rPPG methods require minimal computational resources, enabling real-time implementation on low-compute devices. Our results indicate that the time-averaging sliding frame method achieved the greatest balance between preserving the information within the frame and inducing a heart rate error, with an average error of 22 beats per minute (bpm). Further, the facial region of interest was found to be the most effective and to offer the best trade-off between bpm errors and information loss.

Innovative approaches in imaging photoplethysmography for remote blood oxygen monitoring

Peripheral Capillary Oxygen Saturation (SpO2) has received increasing attention during the COVID-19 pandemic. Clinical investigations have demonstrated that individuals afflicted with COVID-19 exhibit notably reduced levels of SpO2 before the deterioration of their health status. To cost-effectively enable individuals to monitor their SpO2, this paper proposes a novel neural network model named "ITSCAN" based on Temporal Shift Module. Benefiting from the widespread use of smartphones, this model can assess an individual's SpO2 in real time, utilizing standard facial video footage, with a temporal granularity of seconds. The model is interweaved by two distinct branches: the motion branch, responsible for extracting spatiotemporal data features and the appearance branch, focusing on the correlation between feature channels and the location information of feature map using coordinate attention mechanisms. Accordingly, the SpO2 estimator generates the corresponding SpO2 value. This paper summarizes for the first time 5 loss functions commonly used in the SpO2 estimation model. Subsequently, a novel loss function has been contributed through the examination of various combinations and careful selection of hyperparameters. Comprehensive ablation experiments analyze the independent impact of each module on the overall model performance. Finally, the experimental results based on the public dataset (VIPL-HR) show that our model has obvious advantages in MAE (1.10%) and RMSE (1.19%) compared with related work, which implies more accuracy of the proposed method to contribute to public health.

Hospital Environmental Factors That Influence Peripheral Oxygen Saturation Measurements: A Cross-Sectional Study

Pulse oximetry is a non-invasive, cost-effective, and generally reliable instrument measuring pulse rate and peripheral oxygen saturation (SpO2). However, these measurements can be affected by the patient's internal or external factors, including the type of pulse oximeter device (POD). (1) This study's objective was to identify potential environmental factors that may impact the measurements taken by three PODs. (2) Methods: A descriptive-analytical cross-sectional study was designed. The patients' SpO2 levels were measured using a standard monitor and two PODs owned by the professionals. The measurements were taken on the patients' fingers. Concurrently, we evaluated the surrounding environmental conditions, encompassing temperature, humidity, illuminance, and noise. (3) Results: This study involved 288 adult participants in the sample. For each 20-decibel increment in noise, there was a reduction in SpO2 by an average of 1%, whereas for every additional degree of ambient temperature, SpO2 decreased by an average of 2% (4) Conclusions: Significant correlations between SpO2 and age, as well as with noise and ambient temperature, were observed. No significant differences between oxygen saturation and lighting or humidity were observed. This study was prospectively registered with the Clinical Research Ethics Committee of Gran Canaria at the Dr. Negrín University Hospital, with protocol code 2019-247-1, and approved on 24 May 2019.

CL-SPO2Net: Contrastive Learning Spatiotemporal Attention Network for Non-Contact Video-Based SpO2 Estimation

Video-based peripheral oxygen saturation (SpO2) estimation, utilizing solely RGB cameras, offers a non-contact approach to measuring blood oxygen levels. Previous studies set a stable and unchanging environment as the premise for non-contact blood oxygen estimation. Additionally, they utilized a small amount of labeled data for system training and learning. However, it is challenging to train optimal model parameters with a small dataset. The accuracy of blood oxygen detection is easily affected by ambient light and subject movement. To address these issues, this paper proposes a contrastive learning spatiotemporal attention network (CL-SPO2Net), an innovative semi-supervised network for video-based SpO2 estimation. Spatiotemporal similarities in remote photoplethysmography (rPPG) signals were found in video segments containing facial or hand regions. Subsequently, integrating deep neural networks with machine learning expertise enabled the estimation of SpO2. The method had good feasibility in the case of small-scale labeled datasets, with the mean absolute error between the camera and the reference pulse oximeter of 0.85% in the stable environment, 1.13% with lighting fluctuations, and 1.20% in the facial rotation situation.

Using Contactless Facial Image Recognition Technology to Detect Blood Oxygen Saturation

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.

Non-contact oxygen saturation monitoring for wound healing process using dual-wavelength simultaneous acquisition imaging system

Here we report the fabrication of a noncontact pulse oximeter system based on a dual-wavelength imaging system and its oxygen saturation monitoring performance during wound healing. The dual-wavelength imaging system consists of 660 nm and 940 nm light-emitting diodes and a multi-spectral camera that simultaneously accepts visible and near-infrared images. Using the proposed system, images were acquired at 30 fps at both wavelengths, and photoplethysmography signals were extracted by specifying a specific region in the images. We removed the signals caused by small movements and smoothed them using the discrete wavelet transform and moving average filter. To confirm the feasibility of the proposed noncontact oxygen saturation system, a wound model was created using a hairless mouse and oxygen saturation was measured during wound healing. The measured values were compared and analyzed using a reflective animal pulse oximeter. Through a comparative analysis of these two devices, the error of the proposed system was evaluated and the possibility of its clinical application and wound healing monitoring through oxygen saturation measurement confirmed.

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.

Contactless SpO2 with an RGB camera: experimental proof of calibrated SpO2

Camera-based blood oxygen saturation (SpO2) monitoring allows reliable measurements without touching the skin and is therefore very attractive when there is a risk of cross-infection, in case of fragile skin, and/or to improve the clinical workflow. Despite promising results, productization of the technology is hampered by the unavailability of adequate hardware, especially a camera, which can capture the optimal wavelengths for SpO2 measurements in the red near-infrared region. A regular color (RGB) camera is attractive because of its availability, but also poses several risks and challenges which affect the accuracy of the measurement. To mitigate the most important risks, we propose to add low-cost commercial off-the-shelf (COTS) components to the setup. We executed two studies with this setup: one at a hypoxia lab with SpO2 values in the range 70 - 100% with the purpose to determine the calibration model, and the other study on volunteers to investigate the accuracy for different spot-check scenarios. The proposed processing pipeline includes face tracking and a robust method to estimate the ratio of relative amplitudes of the photoplethysmographic waveforms. Results show that the error is smaller than 4 percent points for realistic screening scenarios where the subject is seated, either with or without head support and/or ambient light.

A non-contact oxygen saturation detection method based on dynamic spectrum

Blood oxygen saturation (SpO2) is an important monitoring indicator for many respiratory diseases. Non-contact oximetry offers outstanding advantages in both coronavirus pandemic monitoring and sleep monitoring, but at the same time poses both challenges regarding technology and environment. Therefore, we propose a method for non-contact SpO2 measurement based on the principle of DS (dynamic spectrum) in this paper. A multispectral camera with 24 wavelengths (range in 660 nm-950 nm) is used to capture video of the people's cheek region, and then the two-dimensional images are converted into a one-dimensional temporal PPG signal. After pre-processing the PPG signal, the 24 wavelengths DS values are extracted. The optimal wavelength combination is obtained by wavelength screening using the one-by-one elimination method, and a PLS (partial least squares) model is established using the SpO2 values measured simultaneously by pulse oximetry as the modeled true values. The facial videos of eight healthy subjects were collected, and a total of 140 valid samples were obtained. By analyzing the modeling results, the regression coefficient (R) and root mean square error (RMSE) of the modeled set were 0.6366 and 0.9906, respectively. This method can significantly respond to the variation of SpO2, and the prediction results are approaching to the prediction accuracy (±2%) of most pulse oximeters in the market. Using DS theory in this method eliminates in principle the interference of static tissue, individual differences, and environment. It fully meets the strong demand for non-contact oximetry and provides a new measurement idea.

Photoplethysmographic Imaging of Hemodynamics and Two-Dimensional Oximetry

The review of recent papers devoted to actively developing methods of photoplethysmographic imaging (the PPGI) of blood volume pulsations in vessels and non-contact two-dimensional oximetry on the surface of a human body has been carried out. The physical fundamentals and technical aspects of the PPGI and oximetry have been considered. The manifold of the physiological parameters available for the analysis by the PPGI method has been shown. The prospects of the PPGI technology have been discussed. The possibilities of non-contact determination of blood oxygen saturation SpO2 (pulse saturation O2) have been described. The relevance of remote determination of the level of oxygenation in connection with the spread of a new coronavirus infection SARS-CoV-2 (COVID-19) has been emphasized. Most of the works under consideration cover the period 2010-2021.

Accuracy enhancement in reflective pulse oximetry by considering wavelength-dependent pathlengths

Objective. Noninvasive measurement of oxygen saturation (SpO₂) using pulse oximetry based on transmissive photoplethysmography (tPPG) is clinically accepted and widely employed. However, reflective photoplethysmography (rPPG) - present in smartwatches - has not become equally accepted, partially because the pathlengths of the red and infrared PPGs are patient-dependent. Thus, even the most popular "Ratio of Modulation" (R) method requires patient-dependent calibration to reduce the errors in the measurement of SpO2 using rPPGs.Approach. In this paper, a correction factor or "pathlength ratio" β is introduced in an existing calibration-free algorithm that compensates the patient-dependent pathlength variations, and improved accuracy is obtained in the measurement of SpO2 using rPPGs. The proposed β is derived through the analytical model of a rPPG signal. Using the new expression and data obtained from a human hypoxia study wherein arterial oxygen saturation values acquired through Blood Gas Analysis were employed as a reference, β is determined.Main results. The results of the analysis show that a specific combination of the β and the measurements on the pulsating part of the natural logarithm of the red and infrared PPG signals yields a reduced root-mean-square error (RMSE). It is shown that the average RMSE in measuring SpO2 values reduces to 1 %.Significance. The human hypoxia study data used for this work, obtained in a previous study, coversSpO₂values in the range from 70 % to 100 %, and thus shows that the pathlength ratio β proposed here works well in the range of clinical interest. This work demonstrates that the calibration-free method applicable for transmission type PPGs can be extended to determineSpO₂using reflective PPGs with the incorporation of the correction factor β. Our algorithm significantly reduces the number of parameters needed for the estimation, while keeping the RMSE below the clinically accepted 2 %.

Skin Pigmentation Influence on Pulse Oximetry Accuracy: A Systematic Review and Bibliometric Analysis

Nowadays, pulse oximetry has become the standard in primary and intensive care units, especially as a triage tool during the current COVID-19 pandemic. Hence, a deeper understanding of the measurement errors that can affect precise readings is a key element in clinical decision-making. Several factors may influence the accuracy of pulse oximetry, such as skin color, body temperature, altitude, or patient movement. The skin pigmentation effect on pulse oximetry accuracy has long been studied reporting some contradictory conclusions. Recent studies have shown a positive bias in oxygen saturation measurements in patients with darkly pigmented skin, particularly under low saturation conditions. This review aims to study the literature that assesses the influence of skin pigmentation on the accuracy of these devices. We employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to conduct a systematic review retrospectively since February 2022 using WOS, PubMed, and Scopus databases. We found 99 unique references, of which only 41 satisfied the established inclusion criteria. A bibliometric and scientometrics approach was performed to examine the outcomes of an exhaustive survey of the thematic content and trending topics.

Smart Electrically Assisted Bicycles as Health Monitoring Systems: A Review

This paper aims to provide a review of the electrically assisted bicycles (also known as e-bikes) used for recovery of the rider's physical and physiological information, monitoring of their health state, and adjusting the "medical" assistance accordingly. E-bikes have proven to be an excellent way to do physical activity while commuting, thus improving the user's health and reducing air pollutant emissions. Such devices can also be seen as the first step to help unhealthy sedentary people to start exercising with reduced strain. Based on this analysis, the need to have e-bikes with artificial intelligence (AI) systems that recover and processe a large amount of data is discussed in depth. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used to complete the relevant papers' search and selection in this systematic review.