Camera-based assessment of arterial stiffness and wave reflection parameters from neck micro-motion

Observation of blood motion in the internal jugular vein by contact and contactless photoplethysmography during physiological testing: case studies

Central venous pressure is an estimate of right atrial pressure and is often used to assess hemodynamic status. However, since it is measured invasively, non-invasive alternatives would be of great utility. The aim of this preliminary study was a) to investigate whether photoplethysmography (PPG) can be used to characterize venous system fluid motion and b) to find the model for venous blood volume modulations. For this purpose, we monitored the internal jugular veins using contact (cPPG) and video PPG during clinically validated physiological tests: abdominojugular test (AJT) and breath holding (BH). Video PPG and cPPG signals were captured simultaneously on the left and right sides of the neck, respectively. ECG was also captured using the same clinical monitor as cPPG. Two volunteers underwent AJT and BH with head up/down, each with: baseline (15s), experiment (15s), and recovery (15s). Video PPG was split into remote PPG (rPPG) and micromotion detection. All signal modalities were significantly affected by physiological testing. Moreover, cPPG and micromotion waveforms exhibited primary features of jugular vein waveforms and, therefore, have great potential for venous blood flow monitoring. Specifically, remote patient monitoring applications may be enabled by this methodology, facilitating physical collection without a specially trained care provider.

Capturing the pulse: a state-of-the-art review on camera-based jugular vein assessment

Heart failure is associated with a rehospitalisation rate of up to 50% within six months. Elevated central venous pressure may serve as an early warning sign. While invasive procedures are used to measure central venous pressure for guiding treatment in hospital, this becomes impractical upon discharge. A non-invasive estimation technique exists, where the clinician visually inspects the pulsation of the jugular veins in the neck, but it is less reliable due to human limitations. Video and signal processing technologies may offer a high-fidelity alternative. This state-of-the-art review analyses existing literature on camera-based methods for jugular vein assessment. We summarize key design considerations and suggest avenues for future research. Our review highlights the neck as a rich imaging target beyond the jugular veins, capturing comprehensive cardiac signals, and outlines factors affecting signal quality and measurement accuracy. Addressing an often quoted limitation in the field, we also propose minimum reporting standards for future studies.

Non-contact quantification of aortic stenosis and mitral regurgitation using carotid waveforms from skin displacements

Objective. Early diagnosis of heart problems is essential for improving patient prognosis.Approach. We created a non-contact imaging system that calculates the vessel-induced deformation of the skin to estimate the carotid artery pressure displacement waveforms. We present a clinical study of the system in patients (n= 27) with no underlying condition, aortic stenosis (AS), or mitral regurgitation (MR).Main results. Displacement waveforms were compared to aortic catheter pressures in the same patients. The morphologies of the pressure and displacement waveforms were found to be similar, and pulse wave analysis metrics, such as our modified reflection indices (RI) and waveform duration proportions, showed no significant differences. Compared with the control group, AS patients displayed a greater proportion of time to peak (p= 0.026 andp= 0.047 for catheter and displacement, respectively), whereas augmentation index (AIx)was greater for the displacement waveform only (p= 0.030). The modified RI for MR (p= 0.047 andp= 0.004 for catheter and displacement, respectively) was lower than in the controls. AS and MR were also significantly different for the proportion of time to peak (p= 0.018 for the catheter measurements), RI (p= 0.045 andp= 0.002 for the catheter and displacement, respectively), and AIx (p= 0.005 for the displacement waveform).Significance. These findings demonstrate the ability of our system to provide insights into cardiac conditions and support further development as a diagnostic/telehealth-based screening tool.

Feasibility of Specular Reflection Imaging for Extraction of Neck Vessel Pressure Waveforms

Cardiovascular disease (CVD) is a leading cause of death worldwide and was responsible for 31% of all deaths in 2015. Changes in fluid pressures within the vessels of the circulatory system reflect the mechanical function of the heart. The jugular venous (JV) pulse waveform is an important clinical sign for assessing cardiac function. However, technology able to aid evaluation and interpretation are currently lacking. The goal of the current study was to develop a remote monitoring tool that aid clinicians in robust measurements of JV pulse waveforms. To address this need, we have developed a novel imaging modality, Specular Reflection Vascular Imaging (SRVI). The technology uses specular reflection for visualization of skin displacements caused by pressure pulsations in blood vessels. SRVI has been tested on 10 healthy volunteers. 10-seconds videos of the neck illuminated with a diffuse light source were captured at 250 fps. SRVI was able to identify and discriminate skin displacements caused by carotid artery and jugular vein pulsations to extract both carotid artery and jugular vein waveforms, making them easier to be visualized and interpreted. The method provided a 6-fold improvement in signal strength over a comparator remote PPG dataset. The current pilot study is a proof-of-concept demonstration of the potential of Specular Reflection Vascular Imaging for extraction of JV pulse waveforms.

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.

Impact of makeup on remote-PPG monitoring

Camera-based remote photoplethysmography (remote-PPG) enables contactless measurement of blood volume pulse from the human skin. Skin visibility is essential to remote-PPG as the camera needs to capture the light reflected from the skin that penetrates deep into skin tissues and carries blood pulsation information. The use of facial makeup may jeopardize this measurement by reducing the amount of light penetrating into and reflecting from the skin. In this paper, we conduct an empirical study to thoroughly investigate the impact of makeup on remote-PPG monitoring, in both the visible (RGB) and invisible (Near Infrared, NIR) lighting conditions. The experiment shows that makeup has negative influence on remote-PPG, which reduces the relative PPG strength (AC/DC) at different wavelengths and changes the normalized PPG signature across multiple wavelengths. It makes (i) the pulse-rate extraction more difficult in both the RGB and NIR, although NIR is less affected than RGB, and (ii) the blood oxygen saturation extraction in NIR impossible. To the best of our knowledge, this is the first work that systematically investigate the impact of makeup on camera-based remote-PPG monitoring.

A Broader Look: Camera-Based Vital Sign Estimation across the Spectrum

OBJECTIVES

Camera-based vital sign estimation allows the contactless assessment of important physiological parameters. Seminal contributions were made in the 1930s, 1980s, and 2000s, and the speed of development seems ever increasing. In this suivey, we aim to overview the most recent works in this area, describe their common features as well as shortcomings, and highlight interesting "outliers".

METHODS

We performed a comprehensive literature research and quantitative analysis of papers published between 2016 and 2018. Quantitative information about the number of subjects, studies with healthy volunteers vs. pathological conditions, public datasets, laboratory vs. real-world works, types of camera, usage of machine learning, and spectral properties of data was extracted. Moreover, a qualitative analysis of illumination used and recent advantages in terms of algorithmic developments was also performed.

RESULTS

Since 2016, 116 papers were published on camera-based vital sign estimation and 59% of papers presented results on 20 or fewer subjects. While the average number of participants increased from 15.7 in 2016 to 22.9 in 2018, the vast majority of papers (n=100) were on healthy subjects. Four public datasets were used in 10 publications. We found 27 papers whose application scenario could be considered a real-world use case, such as monitoring during exercise or driving. These include 16 papers that dealt with non-healthy subjects. The majority of papers (n=61) presented results based on visual, red-green-blue (RGB) information, followed by RGB combined with other parts of the electromagnetic spectrum (n=18), and thermography only (n=12), while other works (n=25) used other mono- or polychromatic non-RGB data. Surprisingly, a minority of publications (n=39) made use of consumer-grade equipment. Lighting conditions were primarily uncontrolled or ambient. While some works focused on specialized aspects such as the removal of vital sign information from video streams to protect privacy or the influence of video compression, most algorithmic developments were related to three areas: region of interest selection, tracking, or extraction of a one-dimensional signal. Seven papers used deep learning techniques, 17 papers used other machine learning approaches, and 92 made no explicit use of machine learning.

CONCLUSION

Although some general trends and frequent shortcomings are obvious, the spectrum of publications related to camera-based vital sign estimation is broad. While many creative solutions and unique approaches exist, the lack of standardization hinders comparability of these techniques and of their performance. We believe that sharing algorithms and/ or datasets will alleviate this and would allow the application of newer techniques such as deep learning.

Cardiovascular assessment by imaging photoplethysmography - a review

Over the last few years, the contactless acquisition of cardiovascular parameters using cameras has gained immense attention. The technique provides an optical means to acquire cardiovascular information in a very convenient way. This review provides an overview on the technique's background and current realizations. Besides giving detailed information on the most widespread application of the technique, namely the contactless acquisition of heart rate, we outline further concepts and we critically discuss the current state.

Non-contact Quantification of Jugular Venous Pulse Waveforms from Skin Displacements

The jugular venous (JV) pressure waveform is a non-invasive, proven indicator of cardiovascular disease. Conventional clinical methods for assessing these waveforms are often overlooked because they require specialised expertise, and are invasive and expensive to implement. Recently, image-based methods have been used to quantify JV pulsation waveforms on the skin as an indirect way of estimating the pressure waveforms. However, these existing image-based methods cannot explicitly measure skin deformations and rely on the use of photoplethysmography (PPG) devices for identification of the pulsatile waveforms. As a result, they often have limited accuracy and robustness and are unsuitable in the clinical environment. Here, we propose a technique to directly measure skin deformations caused by the JV pulse using a very accurate subpixel registration algorithm. The method simply requires images obtained from the subject’s neck using a commodity camera. The results show that our measured waveforms contained all of the essential features of diagnostic JV waveforms in all of 19 healthy subjects tested in this study, indicating a significantly important capability for a potential future diagnostic device. The shape of our measured JV displacement waveforms was validated using waveforms measured with a laser displacement sensor, where the average correlation score between the two waveforms was 0.93 ± 0.05. In addition, synchronously recorded ECG signals were used to verify the timings of diagnostic features of the measured waveforms. To our knowledge, this is the first use of image registration for direct measurement of JV displacement waveforms. Significant advantages of our novel method include the high precision of our measurements, and the ability to use ordinary cameras, such as those in modern mobile phones. These advantages will enable the development of affordable and accessible devices to measure JV waveforms for cardiac diagnostics in the clinical environment. Future devices based on this technology may provide viable options for telemedicine applications, point of care diagnostics, and mobile-based cardiac health monitoring systems.