Impact of makeup on remote-PPG monitoring

Multispectral Depolarization Based Living-Skin Detection: A New Measurement Principle

Camera-based photoplethysmographic imaging enabled the segmentation of living-skin tissues in a video, but it has inherent limitations to be used in real-life applications such as video health monitoring and face anti-spoofing. Inspired by the use of polarization for improving vital signs monitoring (i.e. specular reflection removal), we observed that skin tissues have an attractive property of wavelength-dependent depolarization due to its multi-layer structure containing different absorbing chromophores, i.e. polarized light photons with longer wavelengths (R) have deeper skin penetrability and thus experience thorougher depolarization than those with shorter wavelengths (G and B). Thus we proposed a novel dual-polarization setup and an elegant algorithm (named "MSD") that exploits the nature of multispectral depolarization of skin tissues to detect living-skin pixels, which only requires two images sampled at the parallel and cross polarizations to estimate the characteristic chromaticity changes (R/G) caused by tissue depolarization. Our proposal was verified in both the laboratory and hospital settings (ICU and NICU) focused on anti-spoofing and patient skin segmentation. The clinical experiments in ICU also indicate the potential of MSD for skin perfusion analysis, which may lead to a new diagnostic imaging approach in the future.

Assessing heart rate and blood pressure estimation from image photoplethysmography using a digital blood pressure meter

This study presents a non-contact approach to measuring heart rate and blood pressure using an image photoplethysmography (iPPG) signal, and compares the results to those from an oscillometric blood pressure meter. Facial videos of 100 subjects were recorded via a webcam under ambient lighting conditions to extract iPPG signals. The results revealed a strong correlation between the heart rate derived from iPPG and that obtained from an oscillometric blood pressure meter. In addition, a continuous wavelet transform images with a 6-s duration were used as input for a custom convolutional neural network model, providing the most accurate blood pressure estimation. The proposed method received a grade A for diastolic and grade B for systolic blood pressure based on the British Hypertension Society's criteria. It also met the standards set by the Association for the Advancement of Medical Instrumentation. This non-contact framework shows promising potential for efficient screening purposes.

For Heart Rate Assessments from Drone Footage in Disaster Scenarios

The ability to use drones to obtain important vital signs could be very valuable for emergency personnel during mass-casualty incidents. The rapid and robust remote assessment of heart rates could serve as a life-saving decision aid for first-responders. With the flight sensor data of a specialized drone, a pipeline was developed to achieve a robust, non-contact assessment of heart rates through remote photoplethysmography (rPPG). This robust assessment was achieved through adaptive face-aware exposure and comprehensive de-noising of a large number of predicted noise sources. In addition, we performed a proof-of-concept study that involved 18 stationary subjects with clean skin and 36 recordings of their vital signs, using the developed pipeline in outdoor conditions. In this study, we could achieve a single-value heart-rate assessment with an overall root-mean-squared error of 14.3 beats-per-minute, demonstrating the basic feasibility of our approach. However, further research is needed to verify the applicability of our approach in actual disaster situations, where remote photoplethysmography readings could be impacted by other factors, such as blood, dirt, and body positioning.

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still not straightforward. The best algorithm selection improves the signal-to-noise ratio (SNR) and therefore improves the accuracy of the recognition and classification of vital signs. We recorded more than 300 temporal rPPG signals where the noise was not motion-induced. Then, we investigated the best digital filter in pre-processing temporal rPPG data and compared the performances of 10 filters with 10 orders each (i.e., a total of 100 filters). The performances are assessed using a signal quality metric on three levels. The quality of the raw signals was classified under three categories; Q1 being the best and Q3 being the worst. The results are presented in SNR scores, which show that the Chebyshev II orders of 2nd, 4th, and 6th perform the best for denoising rPPG signals.

Effects of illuminance intensity on the green channel of remote photoplethysmography (rPPG) signals

Point-of-care remote photoplethysmography (rPPG) devices that utilize low-cost RGB cameras have drawn considerable attention due to their convenience in contactless and non-invasive vital signs monitoring. In rPPG, sufficient lighting conditions are essential for obtaining accurate diagnostics by observing the complete signal morphology. The effects of illuminance intensity and light source settings play a significant role in rPPG assessment quality, and it was previously observed that different lighting schemes result in different signal quality and morphology. This study presents a quantitative empirical analysis where the quality and morphology of rPPG signals were assessed under different light settings. Participants' faces were exposed to the white LED spotlight, first when the sources were installed directly behind the video camera, and then when the sources were installed in a cross-polarized scheme. Hence, the effect of specular reflectance on rPPG signals could be observed in an increasing projection. The signal qualities were analyzed in each intensity level using a signal-to-noise (SNR) ratio metric. In 3 of 7 participants, placing the video camera on the same level as the light source led to signal quality loss of up to 3 dB for the range 30-60 Lux. In addition, two fundamental morphological features were analyzed, and the derivative-related feature was found to be increasing with illuminance intensity in 6 of 7 participants.

Blood Pressure Measurement: From Cuff-Based to Contactless Monitoring

Blood pressure (BP) determines whether a person has hypertension and offers implications as to whether he or she could be affected by cardiovascular disease. Cuff-based sphygmomanometers have traditionally provided both accuracy and reliability, but they require bulky equipment and relevant skills to obtain precise measurements. BP measurement from photoplethysmography (PPG) signals has become a promising alternative for convenient and unobtrusive BP monitoring. Moreover, the recent developments in remote photoplethysmography (rPPG) algorithms have enabled new innovations for contactless BP measurement. This paper illustrates the evolution of BP measurement techniques from the biophysical theory, through the development of contact-based BP measurement from PPG signals, and to the modern innovations of contactless BP measurement from rPPG signals. We consolidate knowledge from a diverse background of academic research to highlight the importance of multi-feature analysis for improving measurement accuracy. We conclude with the ongoing challenges, opportunities, and possible future directions in this emerging field of research.

Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review

In recent years, noncontact measurements of vital signs using cameras received a great amount of interest. However, some questions are unanswered: (i) Which vital sign is monitored using what type of camera? (ii) What is the performance and which factors affect it? (iii) Which health issues are addressed by camera-based techniques? Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement, we conduct a systematic review of continuous camera-based vital sign monitoring using Scopus, PubMed, and the Association for Computing Machinery (ACM) databases. We consider articles that were published between January 2018 and April 2021 in the English language. We include five vital signs: heart rate (HR), respiratory rate (RR), blood pressure (BP), body skin temperature (BST), and oxygen saturation (SpO2). In total, we retrieve 905 articles and screened them regarding title, abstract, and full text. One hundred and four articles remained: 60, 20, 6, 2, and 1 of the articles focus on HR, RR, BP, BST, and SpO2, respectively, and 15 on multiple vital signs. HR and RR can be measured using red, green, and blue (RGB) and near-infrared (NIR) as well as far-infrared (FIR) cameras. So far, BP and SpO2 are monitored with RGB cameras only, whereas BST is derived from FIR cameras only. Under ideal conditions, the root mean squared error is around 2.60 bpm, 2.22 cpm, 6.91 mm Hg, 4.88 mm Hg, and 0.86 °C for HR, RR, systolic BP, diastolic BP, and BST, respectively. The estimated error for SpO2 is less than 1%, but it increases with movements of the subject and the camera-subject distance. Camera-based remote monitoring mainly explores intensive care, post-anaesthesia care, and sleep monitoring, but also explores special diseases such as heart failure. The monitored targets are newborn and pediatric patients, geriatric patients, athletes (e.g., exercising, cycling), and vehicle drivers. Camera-based techniques monitor HR, RR, and BST in static conditions within acceptable ranges for certain applications. The research gaps are large and heterogeneous populations, real-time scenarios, moving subjects, and accuracy of BP and SpO2 monitoring.

Towards Development of Specular Reflection Vascular Imaging

Specular reflection from tissue is typically considered as undesirable, and managed through device design. However, we believe that specular reflection is an untapped light-tissue interaction, which can be used for imaging subcutaneous blood flow. To illustrate the concept of subcutaneous blood flow visualization using specular reflection from the skin, we have developed a ray tracing for the neck and identified conditions under which useful data can be collected. Based on our model, we have developed a prototype Specular Reflection Vascular Imaging (SRVI) device and demonstrated its feasibility by imaging major neck vessels in a case study. The system consists of a video camera that captures a video from a target area illuminated by a rectangular LED source. We extracted the SRVI signal from 5 × 5 pixels areas (local SRVI signal). The correlations of local SRVIs to the SRVI extracted from all pixels in the target area do not appear to be randomly distributed, but rather form cohesive sub-regions with distinct boundaries. The obtained waveforms were compared with the ECG signal. Based on the time delays with respect to the ECG signal, as well as the waveforms themselves, the sub-regions can be attributed to the jugular vein and carotid artery. The proposed method, SRVI, has the potential to contribute to extraction of the diagnostic information that the jugular venous pulse can provide.

Fundamentals of Camera-PPG based Magnetic Resonance Imaging

In Magnetic Resonance Imaging (MRI), cardiac triggering that synchronizes data acquisition with cardiac contractions is an essential technique for acquiring high-quality images. Triggering is typically based on the Electrocardiogram (ECG) signal (e.g. R-peak). Since ECG acquisition involves extra workflow steps like electrode placement and ECG signals are usually disturbed by magnetic fields in high Magnetic Resonance (MR) systems, we explored camera-based photoplethysmography (PPG) as an alternative. We used the in-bore camera of a clinical MR system to investigate the feasibility and challenges of camera-based cardiac triggering. Data from ECG, finger oximeter and camera were synchronously collected. We found that that camera-PPG provides a higher availability of signal (and trigger) measurement, and the PPG signals measured from the forehead show considerably less delay w.r.t. the coupled ECG R-peak than the finger PPG signals in terms of trigger detection. The insights obtained in this study provide a basis for an envisioned system design phase.