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Clinical applications for imaging photoplethysmography
Abstract
Most of the work related to imaging photoplethysmography (iPPG) has its focus on methodological developments. To date, only few investigations addressed clinical applications. This chapter reviews the clinical usability of the iPPG. We present a number of potential applications together with their clinical background and relevant works. Covered applications comprise iPPG's use for patient monitoring and diagnostic applications beyond patient monitoring, particularly based on iPPG's capability for two-dimensional analyses of cutaneous perfusion. Finally, we provide an outlook on future clinical use cases and required developments.
... The technique exploits subtle variations in the intensity of reflected light, which varies with blood filling of superficial vessels. Multiple current reviews provide good overviews on the fundamentals and applications of iPPG Molinaro et al. (2022); Selvaraju et al. (2022); Shao et al. (2021); Zaunseder and Rasche (2022). According to them, the vast majority of available works in the field of iPPG direct at heart rate and heart rate variability. ...
Photoplethysmography (PPG) allows various statements about the physiological state. It supports multiple recording setups, i.e., application to various body sites and different acquisition modes, rendering the technique a versatile tool for various situations. Owing to anatomical, physiological and metrological factors, PPG signals differ with the actual setup. Research on such differences can deepen the understanding of prevailing physiological mechanisms and path the way towards improved or novel methods for PPG analysis. The presented work systematically investigates the impact of the cold pressor test (CPT), i.e., a painful stimulus, on the morphology of PPG signals considering different recording setups. Our investigation compares contact PPG recorded at the finger, contact PPG recorded at the earlobe and imaging PPG (iPPG), i.e., non-contact PPG, recorded at the face. The study bases on own experimental data from 39 healthy volunteers. We derived for each recording setup four common morphological PPG features from three intervals around CPT. For the same intervals, we derived blood pressure and heart rate as reference. To assess differences between the intervals, we used repeated measures ANOVA together with paired t-tests for each feature and we calculated Hedges’ g to quantify effect sizes. Our analyses show a distinct impact of CPT. As expected, blood pressure shows a highly significant and persistent increase. Independently of the recording setup, all PPG features show significant changes upon CPT as well. However, there are marked differences between recording setups. Effect sizes generally differ with the finger PPG showing the strongest response. Moreover, one feature (pulse width at half amplitude) shows an inverse behavior in finger PPG and head PPG (earlobe PPG and iPPG). In addition, iPPG features behave partially different from contact PPG features as they tend to return to baseline values while contact PPG features remain altered. Our findings underline the importance of recording setup and physiological as well as metrological differences that relate to the setups. The actual setup must be considered in order to properly interpret features and use PPG. The existence of differences between recording setups and a deepened knowledge on such differences might open up novel diagnostic methods in the future.
Remote imaging photoplethysmography (iPPG) senses the cardiac pulse in outer skin layers and is responsive to mean arterial pressure and pulse pressure in critically ill patients. Whether iPPG is sufficiently sensitive to monitor cutaneous perfusion is not known. This study aimed at determining the response of iPPG to changes in cutaneous perfusion measured by Laser speckle imaging (LSI). Thirty-seven volunteers were engaged in a cognitive test known to evoke autonomic nervous activity and a Heat test. Simultaneous measurements of iPPG and LSI were taken at baseline and during cutaneous perfusion challenges. A perfusion index (PI) was calculated to assess iPPG signal strength. The response of iPPG to the challenges and its relation to LSI were determined. PI of iPPG significantly increased in response to autonomic nervous stimuli and to the Heat test by 5.8% (p = 0.005) and 11.1% (p < 0.001), respectively. PI was associated with LSI measures of cutaneous perfusion throughout experiments (p < 0.001). iPPG responses to study task correlated with those of LSI (r = 0.62, p < 0.001) and were comparable among subjects. iPPG is sensitive to autonomic nervous activity in volunteers and is closely associated with cutaneous perfusion.
Imaging photoplethysmography (iPPG) is a contact-free monitoring of the cutaneous blood volume pulse by RGB (red-green-blue) cameras. It detects vital parameters from skin areas and is associated to cutaneous perfusion. This study investigated the use of iPPG to quantify changes in cutaneous perfusion after major surgery. Patients undergoing coronary artery bypass grafting (CABG) were scanned before surgery and in three follow-up measurements. Using an industrial-grade RGB camera and usual indoor lighting, a contact-free imaging plethysmogram from the chest was obtained. Changes of the iPPG signal strength were evaluated in view of both the operation itself as well as the unilateral preparation of the internal thoracic artery (ITA) for coronary artery grafting, which is the main blood source of the chest wall. iPPG signal strength globally decreased after surgery and recovered partially during the follow up measurements. The ITA preparation led to a deeper decrease and an attenuated recovery of the iPPG signal strength compared to the other side of the chest wall. These results comply with the expected changes of cutaneous perfusion after CABG using an ITA graft. iPPG can be used to assess cutaneous perfusion and its global changes after major surgery as well as its local changes after specific surgical procedures.
Photplethysmography (PPG) is known to reflect changes in sympathetic tone. This contribution investigates the behaviour of imaging photoplethysmography (iPPG) upon sympathetic activation. To that end, we assessed the impact of a distal painful stimulus on the facial iPPG and con-tralateral finger PPG waveforms. Our results show that alternating components of both signals behave differently. As expected, the alternating component of the finger PPG signal shows a significant and persistent decrease upon stimulus (p < 0.001). The alternating component of the iPPG signal shows only a slight decrease followed by a fast increase (p < 0.01). The found behaviour might be explained by different degrees of sympathetic responsiveness in the extremities and in the face. Sympathetic activation increases cardiac output and triggers general vasoconstriction. Extremities show highly pronounced vasoconstriction which decreases the alternating component. The facial vasocon-striction is comparatively small. As a result, local vasocon-striction might cause a short-term decrease followed by the contrary effect, namely an increase in the alternating component , driven by an increased systemic pulse pressure. Our finding has relevance for the interpretation of iPPG signals and the design of future use cases beyond remote heart rate assessment. In particular, care should be taken when expectations on the finger PPG are to be transferred to iPPG.
We investigate the regulation of human brain arousal in the central nervous system and its synchronization with the autonomic nervous system affecting the facial dynamics and its behavioral gestalt. A major focus is made on the sensing observable during natural human eye to eye communication. Although the inner state of the autopoietic system is deterministic, its outer facial behavioral component non-deterministic. Beside the introduction of general validity of the classical empirical interpretation of the vigilance continuum during open eyes, we show that the facial behavior can be used as suitable surrogate measurement for specific states of mind. As a consequence we predict brainwaves from face videos formulated as inverse problem of the underlying stochastic process. Finally, we discuss the impact and range of application field.
Background: In the last two decades, infrared thermography (IRT) has been applied in quarantine stations for the screening of patients with suspected infectious disease. However, the fever-based screening procedure employing IRT suffers from low sensitivity, because monitoring body temperature alone is insufficient for detecting infected patients. To overcome the drawbacks of fever-based screening, this study aims to develop and evaluate a multiple vital sign (i.e., body temperature, heart rate and respiration rate) measurement system using RGB-thermal image sensors. Methods: The RGB camera measures blood volume pulse (BVP) through variations in the light absorption from human facial areas. IRT is used to estimate the respiration rate by measuring the change in temperature near the nostrils or mouth accompanying respiration. To enable a stable and reliable system, the following image and signal processing methods were proposed and implemented: (1) an RGB-thermal image fusion approach to achieve highly reliable facial region-of-interest tracking, (2) a heart rate estimation method including a tapered window for reducing noise caused by the face tracker, reconstruction of a BVP signal with three RGB channels to optimize a linear function, thereby improving the signal-to-noise ratio and multiple signal classification (MUSIC) algorithm for estimating the pseudo-spectrum from limited time-domain BVP signals within 15 s and (3) a respiration rate estimation method implementing nasal or oral breathing signal selection based on signal quality index for stable measurement and MUSIC algorithm for rapid measurement. We tested the system on 22 healthy subjects and 28 patients with seasonal influenza, using the support vector machine (SVM) classification method. Results: The body temperature, heart rate and respiration rate measured in a non-contact manner were highly similarity to those measured via contact-type reference devices (i.e., thermometer, ECG and respiration belt), with Pearson correlation coefficients of 0.71, 0.87 and 0.87, respectively. Moreover, the optimized SVM model with three vital signs yielded sensitivity and specificity values of 85.7% and 90.1%, respectively. Conclusion: For contactless vital sign measurement, the system achieved a performance similar to that of the reference devices. The multiple vital sign-based screening achieved higher sensitivity than fever-based screening. Thus, this system represents a promising alternative for further quarantine procedures to prevent the spread of infectious diseases.
Objective:
Instrumental identification of proximal scleroderma, which is necessary for the early diagnosis of systemic sclerosis (SSD), has not yet been developed. The aim of this study was to assess the potential diagnostic value of the imaging photoplethysmography (IPPG) method in patients with SSD.
Approach:
The study enrolled 19 patients with SSD and 21 healthy subjects matched by age and sex with the patients. Spatial distribution of capillary-blood-flow parameters and their dynamics was estimated in the facial area of patients and subjects. In the IPPG system, a 40-s video of the subject's face illuminated by green polarized light was recorded with a monochrome digital camera in synchronization with the electrocardiogram. Experimental data were processed by using custom software allowing assessment of an arrival time of the blood pressure wave (PAT), an amplitude of pulsatile component (APC) of the photoplethysmographic waveform, and their variability.
Main results:
Our study has revealed significant increase of PAT variability in patients with SSD compared to the control group: 52±47 ms vs 24±13 ms (P = 0.01). Similarly, the variability of PPG-pulse shape was larger in patients with SSD: 0.13±0.07 % vs 0.09±0.02 % (P < 0.001). In addition, patients with scleroderma showed significantly greater degree of asymmetry of APC parameter than the control group: 17.7±9.7 vs 7.9±5.0 (P < 0.001). At the same time, no correlation was found between the photoplethysmographic waveform parameters and either the form or duration of the disease. No relationship between the characteristics of the PPG waveform and the modified Rodnan skin score was found, as well.
Significance:
Novel instrumental markers found in our pilot study showed that the IPPG method can be used for diagnosing the systemic sclerosis in the early stages of the disease.
Background: Hyperspectral Imaging (HSI) has a strong potential to be established as a new contact-free measuring method in medicine. Hyperspectral cameras and data processing have to fulfill requirements concerning practicability and validity to be integrated in clinical routine processes. Methods: Calculating physiological parameters which are of significant clinical value from recorded remission spectra is a complex challenge. We present a data processing method for HSI remission spectra based on a five-layer model of perfused tissue that generates perfusion parameters for every layer and presents them as depth profiles. The modeling of the radiation transport and the solution of the inverse problem are based on familiar approximations, but use partially heuristic methods for efficiency and to fulfill practical clinical requirements. Results: The parameter determination process is consistent, as the measured spectrum is practically completely reproducible by the modeling sequence; in other words, the whole spectral information is transformed into model parameters which are easily accessible for physiological interpretation. The method is flexible enough to be applicable on a wide spectrum of skin and wounds. Examples of advanced procedures utilizing extended perfusion representation in clinical application areas (flap control, burn diagnosis) are presented.
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.
Background:
Cuff-based blood pressure measurement lacks comfort and convenience. Here, we examined whether blood pressure can be determined in a contactless manner using a novel smartphone-based technology called transdermal optical imaging. This technology processes imperceptible facial blood flow changes from videos captured with a smartphone camera and uses advanced machine learning to determine blood pressure from the captured signal.
Methods:
We enrolled 1328 normotensive adults in our study. We used an advanced machine learning algorithm to create computational models that predict reference systolic, diastolic, and pulse pressure from facial blood flow data. We used 70% of our data set to train these models and 15% of our data set to test them. The remaining 15% of the sample was used to validate model performance.
Results:
We found that our models predicted blood pressure with a measurement bias±SD of 0.39±7.30 mm Hg for systolic pressure, -0.20±6.00 mm Hg for diastolic pressure, and 0.52±6.42 mm Hg for pulse pressure, respectively.
Conclusions:
Our results in normotensive adults fall within 5±8 mm Hg of reference measurements. Future work will determine whether these models meet the clinically accepted accuracy threshold of 5±8 mm Hg when tested on a full range of blood pressures according to international accuracy standards.
This paper presents non-contact vital sign monitoring in neonates, based on image processing, where a standard color camera captures the plethysmographic signal and the heart and breathing rates are processed and estimated online. It is important that the measurements are taken in a non-invasive manner, which is imperceptible to the patient. Currently, many methods have been proposed for non-contact measurement. However, to the best of the authors’ knowledge, it has not been possible to identify methods with low computational costs and a high tolerance to artifacts. With the aim of improving contactless measurement results, the proposed method based on the computer vision technique is enhanced to overcome the mentioned drawbacks. The camera is attached to an incubator in the Neonatal Intensive Care Unit and a single area in the neonate’s diaphragm is monitored. Several factors are considered in the stages of image acquisition, as well as in the plethysmographic signal formation, pre-filtering and filtering. The pre-filter step uses numerical analysis techniques to reduce the signal offset. The proposed method decouples the breath rate from the frequency of sinus arrhythmia. This separation makes it possible to analyze independently any cardiac and respiratory dysrhythmias. Nine newborns were monitored with our proposed method. A Bland-Altman analysis of the data shows a close correlation of the heart rates measured with the two approaches (correlation coefficient of 0.94 for heart rate (HR) and 0.86 for breath rate (BR)) with an uncertainty of 4.2 bpm for HR and 4.9 for BR (k = 1). The comparison of our method and another non-contact method considered as a standard independent component analysis (ICA) showed lower central processing unit (CPU) usage for our method (75% less CPU usage).
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.
Current routines for the monitoring of sleep require many sensors attached to the patient during a nocturnal observational study, limiting mobility and causing stress and discomfort. Cameras have shown promise in the remote monitoring of pulse rate, respiration and oxygen saturation, which potentially allows a reduction in the number of sensors. Applying these techniques in a sleep setting is challenging , as it is unknown upfront which portion of the skin will be visible, there is no unique skin-color outside the visible range, and the pulsatility is low in infrared. We present a fully-automatic living tissue detection method to enable continuous monitoring of pulse rate and oxygen saturation during sleep. The system is validated on a dataset where various typical sleep scenarios have been simulated. Results show the proposed method to outperform the current state-of-the-art, especially for the estimation of oxygen saturation .
Camera-based pulse-oximetry has recently shown to be feasible, even when the signal is corrupted by noise and motion artifacts. Earlier work showed that using three instead of the common two wavelengths improves robustness of the measurement, however without a thorough investigation on the optimal wavelength selection. We therefore performed a search to identify these wavelengths to further improve the robustness of the measurement. Besides motion, it is empirically known that there are several other factors that influence the measurement leading to falsely-low or falsely-high SpO2 readings. These factors include the presence of dyshemoglobins or other species. In this paper, we use a theoretical skin-model to study how these factors influence the measurement, and how a proper wavelength selection can reduce the impact on the measurement. Additionally, we show that adding a third wavelength does not only improve robustness, but can also be exploited to create a reliability index for the measurement. Finally, we show that the presence of dyshemoglobins in arterial blood can not only be detected but also quantified. We illustrate this by comparing the estimated COHb levels of a small group of smokers and non-smokers, which typically have different CO-levels.
Camera-based photoplethysmography (cbPPG) is an innovative measuring technique that enables the remote extraction of vital signs using video cameras. Most studies in the field focus on heart rate detection while other physiological quantities are often ignored. In this work, we analyzed the relation between the pulse pressure and the pulsation strengths of cbPPG signals for 70 patients after surgery. Our results show a high correlation between the two measures (r = 0.54). Furthermore, the influence of technical and medical factors was tested. The controlled impact of these factors proved to enhance the correlation by between 9 and 27 %.
Parameters related to macrocirculation, such as the mean arterial pressure, central venous pressure, cardiac output, mixed venous saturation and central oxygen saturation, are commonly used in the hemodynamic assessment of critically ill patients. However, several studies have shown that there is a dissociation between these parameters and the state of microcirculation in this group of patients. Techniques that allow direct viewing of the microcirculation are not completely disseminated, nor are they incorporated into the clinical management of patients in shock. The numerous techniques developed for microcirculation assessment include clinical assessment (e.g., peripheral perfusion index and temperature gradient), laser Doppler flowmetry, tissue oxygen assessment electrodes, videomicroscopy (orthogonal polarization spectral imaging, sidestream dark field imaging or incident dark field illumination) and near infrared spectroscopy. In the near future, the monitoring and optimization of tissue perfusion by direct viewing and microcirculation assessment may become a goal to be achieved in the hemodynamic resuscitation of critically ill patients.
Simple and inexpensive remote photoplethysmography system for monitoring the effectiveness of regional anesthesia was developed and tested. The system involves surgical lamp as light source, compact video camera and computer with custom developed software. Data from eight patients were processed and the effectiveness of regional anesthesia was calculated. The results showed that the standard surgical lamp can be used as a light source together with camera for remote monitoring of regional anesthesia effectiveness.
Occlusion plethysmography is an important method for assessment of the status of the cardiovascular system, which provides valuable information concerning arterial and venous blood flow, including mechanisms of their regulation. All up-to-date systems estimate change of the limb's volume during occlusion by contact-type sensors. The objective of the research is demonstration of feasibility of the novel approach to measuring the blood flow during venous occlusion by using imaging photoplethysmography (PPG). Twenty healthy individuals participated in the experiment. We used four synchronized video cameras to record all-around view of the forearm illuminated by the green light. After the recording, the PPG waveform was calculated in more than 4000 non-overlapping Regions of Interest (ROI). In the most of the ROIs, the waveform shape was typical for classical plethysmography with the distinctive linear growth of the signal. Speed of the signal change was the same along the forearm but it varied along the forearm's circumference. These findings allows us to hypothesize that the PPG waveform is the direct consequence of the forearm blood flow. Therefore, the novel technique could be applied to the same medical examinations as the classical plethysmography, but it is more advantageous because of non-contact nature and easiness in implementation.
Critically ill patients are often hemodynamically unstable (or at risk of becoming unstable) owing to hypovolemia, cardiac dysfunction, or alterations of vasomotor function, leading to organ dysfunction, deterioration into multi-organ failure, and eventually death. With hemodynamic monitoring, we aim to guide our medical management so as to prevent or treat organ failure and improve the outcomes of our patients. Therapeutic measures may include fluid resuscitation, vasopressors, or inotropic agents. Both resuscitation and de-resuscitation phases can be guided using hemodynamic monitoring. This monitoring itself includes several different techniques, each with its own advantages and disadvantages, and may range from invasive to less- and even non-invasive techniques, calibrated or non-calibrated. This article will discuss the indications and basics of monitoring, further elaborating on the different techniques of monitoring.
Background
Accurate synchronization between magnetic resonance imaging data acquisition and a subject’s cardiac activity (“triggering”) is essential for reducing image artifacts but conventional, contact-based methods for this task are limited by several factors, including preparation time, patient inconvenience, and susceptibility to signal degradation. The purpose of this work is to evaluate the performance of a new contact-free triggering method developed with the aim to eventually replace conventional methods in non-cardiac imaging applications. In this study, the method’s performance is evaluated in the context of 7 Tesla non-enhanced angiography of the lower extremities.
Methods
Our main contribution is a basic algorithm capable of estimating in real-time the phase of the cardiac cycle from reflection photoplethysmography signals obtained from skin color variations of the forehead recorded with a video camera. Instead of finding the algorithm’s parameters heuristically, they were optimized using videos of the forehead as well as electrocardiography and pulse oximetry signals that were recorded from eight healthy volunteers in and outside the scanner, with and without active radio frequency and gradient coils. Based on the video characteristics, synthetic signals were generated and the “best available” values of an objective function were determined using mathematical optimization. The performance of the proposed method with optimized algorithm parameters was evaluated by applying it to the recorded videos and comparing the computed triggers to those of contact-based methods. Additionally, the method was evaluated by using its triggers for acquiring images from a healthy volunteer and comparing the result to images obtained using pulse oximetry triggering.
Results
During evaluation of the videos recorded inside the bore with active radio frequency and gradient coils, the pulse oximeter triggers were labeled in 62.5% as “potentially usable” for cardiac triggering, the electrocardiography triggers in 12.5%, and the proposed method’s triggers in 62.5%. Evaluation of the angiography images demonstrated that under appropriate conditions the method is feasible to produce an image quality comparable to pulse oximetry.
Conclusion
We conclude that cardiac triggering using the proposed method is technically feasible. However, for improved reliability the signal-to-noise ratio of the videos will have to be addressed by either replacing the camera sensor, improving the illumination, or by use of additional signal filtering techniques.
Continuous monitoring of respiration is essential for early detection of critical illness. Current methods require sensors attached to the body and/or are not robust to subject motion. Alternative camera-based solutions have been presented using motion vectors and remote photoplethysmography. In this work, we present a non-contact camera-based method to detect respiration, which can operate in both visible and dark lighting conditions by detecting the respiratory-induced colour differences of the skin. We make use of the close similarity between skin colour variations caused by the beating of the heart and those caused by respiration, leading to a much improved signal quality compared to single-channel approaches. Essentially, we propose to find the linear combination of colour channels which suppresses the distortions best in a frequency band including pulse rate, and subsequently we use this same linear combination to extract the respiratory signal in a lower frequency band. Evaluation results obtained from recordings on healthy subjects which perform challenging scenarios, including motion, show that respiration can be accurately detected over the entire range of respiratory frequencies, with a correlation coefficient of 0.96 in visible light and 0.98 in infrared, compared to 0.86 with the best-performing non-contact benchmark algorithm. Furthermore, evaluation on a set of videos recorded in a Neonatal Intensive Care Unit (NICU) shows that this technique looks promising as a future alternative to current contact-sensors showing a correlation coefficient of 0.87.
Camera-based photoplethysmography (cbPPG) is a novel technique that allows the contactless acquisition of cardio-respiratory signals. Previous works on cbPPG most often focused on heart rate extraction. This contribution is directed at the assessment of vasomotor activity by means of cameras. In an experimental study, we show that vasodilation and vasoconstriction both lead to significant changes in cbPPG signals. Our findings underline the potential of cbPPG to monitor vasomotor functions in real-life applications.
We present a noncontact method to measure Ballistocardiogram (BCG) and Photoplethysmogram (PPG) simultaneously using a single camera. The method tracks the motion of facial features to determine displacement BCG, and extracts the corresponding velocity and acceleration BCGs by taking first and second temporal derivatives from the displacement BCG, respectively. The measured BCG waveforms are consistent with those reported in literature and also with those recorded with an accelerometer-based reference method. The method also tracks PPG based on the reflected light from the same facial region, which makes it possible to track both BCG and PPG with the same optics. We verify the robustness and reproducibility of the noncontact method with a small pilot study with 23 subjects. The presented method is the first demonstration of simultaneous BCG and PPG monitoring without wearing any extra equipment or marker by the subject.
BACKGROUND
Contactless, camera-based photoplethysmography (PPG) interrogates shallower skin layers than conventional contact probes, either transmissive or reflective. This raises questions on the calibratability of camera-based pulse oximetry.
METHODS
We made video recordings of the foreheads of 41 healthy adults at 660 and 840 nm, and remote PPG signals were extracted. Subjects were in normoxic, hypoxic, and low temperature conditions. Ratio-of-ratios were compared to reference Spo2 from 4 contact probes.
RESULTS
A calibration curve based on artifact-free data was determined for a population of 26 individuals. For an Spo2 range of approximately 83% to 100% and discarding short-term errors, a root mean square error of 1.15% was found with an upper 99% one-sided confidence limit of 1.65%. Under normoxic conditions, a decrease in ambient temperature from 23 to 7°C resulted in a calibration error of 0.1% (±1.3%, 99% confidence interval) based on measurements for 3 subjects. PPG signal strengths varied strongly among individuals from about 0.9 × 10⁻³ to 4.6 × 10⁻³ for the infrared wavelength.
CONCLUSIONS
For healthy adults, the results present strong evidence that camera-based contactless pulse oximetry is fundamentally feasible because long-term (eg, 10 minutes) error stemming from variation among individuals expressed as A*rms is significantly lower (<1.65%) than that required by the International Organization for Standardization standard (<4%) with the notion that short-term errors should be added. A first illustration of such errors has been provided with A**rms = 2.54% for 40 individuals, including 6 with dark skin. Low signal strength and subject motion present critical challenges that will have to be addressed to make camera-based pulse oximetry practically feasible.
Individuals with obstructive sleep apnea (OSA) can experience partial or complete collapse of the upper airway during sleep. This condition affects between 10-17% of adult men and 3-9% of adult women, requiring arousal to resume regular breathing. Frequent arousals disrupt proper sleeping patterns and cause daytime sleepiness. Untreated OSA has been linked to serious medical issues including cardiovascular disease and diabetes. Unfortunately, diagnosis rates are low (~20%) and current sleep monitoring options are expensive, time-consuming, and uncomfortable. Towards the development of a convenient, non-contact OSA monitoring system, this paper presents a simple, computer vision-based method to monitor cardiopulmonary signals (respiratory and heart rates) during sleep. System testing was performed with 17 healthy participants in five different simulated sleep positions. To monitor cardiopulmonary rates, distinctive points are automatically detected and tracked in infrared image sequences. Blind source separation is applied to extract candidate signals of interest. The optimal respiratory and heart rates are determined using periodicity measures based on spectral analysis. Estimates were validated by comparison to polysomnography recordings. The system achieved a mean percentage error of 3.4% and 5.0% for respiratory rate and heart rate respectively. This study represents an important step in building an accessible, unobtrusive solution for sleep apnea diagnosis.
Cardiovascular monitoring is important to prevent diseases from progressing. The jugular venous pulse (JVP) waveform offers important clinical information about cardiac health, but is not routinely examined due to its invasive catheterisation procedure. Here, we demonstrate for the first time that the JVP can be consistently observed in a non-contact manner using a novel light-based photoplethysmographic imaging system, coded hemodynamic imaging (CHI). While traditional monitoring methods measure the JVP at a single location, CHI's wide-field imaging capabilities were able to observe the jugular venous pulse's spatial flow profile for the first time. The important inflection points in the JVP were observed, meaning that cardiac abnormalities can be assessed through JVP distortions. CHI provides a new way to assess cardiac health through non-contact light-based JVP monitoring, and can be used in non-surgical environments for cardiac assessment.
Significance: Burn assessments, including extent and severity, are some of the most critical diagnoses in burn care, and many recently developed imaging techniques may have the potential to improve the accuracy of these evaluations. Recent Advances: Optical devices, telemedicine, and high-frequency ultrasound are among the highlights in recent burn imaging advancements. We present another promising technology, multispectral imaging (MSI), which also has the potential to impact current medical practice in burn care, among a variety of other specialties. Critical Issues: At this time, it is still a matter of debate as to why there is no consensus on the use of technology to assist burn assessments in the United States. Fortunately, the availability of techniques does not appear to be a limitation. However, the selection of appropriate imaging technology to augment the provision of burn care can be difficult for clinicians to navigate. There are many technologies available, but a comprehensive review summarizing the tissue characteristics measured by each technology in light of aiding clinicians in selecting the proper device is missing. This would be especially valuable for the nonburn specialists who encounter burn injuries. Future Directions: The questions of when burn assessment devices are useful to the burn team, how the various imaging devices work, and where the various burn imaging technologies fit into the spectrum of burn care will continue to be addressed. Technologies that can image a large surface area quickly, such as thermography or laser speckle imaging, may be suitable for initial burn assessment and triage. In the setting of presurgical planning, ultrasound or optical microscopy techniques, including optical coherence tomography, may prove useful. MSI, which actually has origins in burn care, may ultimately meet a high number of requirements for burn assessment in routine clinical use.
Recent studies demonstrated that blood pressure (BP) can be estimated using pulse transit time (PTT). For PTT calculation, photoplethysmogram (PPG) is usually used to detect a time lag in pulse wave propagation which is correlated with BP. Until now, PTT and PPG were registered using a set of body-worn sensors. In this study a new methodology is introduced allowing contactless registration of PTT and PPG using high speed camera resulting in corresponding image-based PTT (iPTT) and image-based PPG (iPPG) generation. The iPTT value can be potentially utilized for blood pressure estimation however extent of correlation between iPTT and BP is unknown. The goal of this preliminary feasibility study was to introduce the methodology for contactless generation of iPPG and iPTT and to make initial estimation of the extent of correlation between iPTT and BP “in vivo.” A short cycling exercise was used to generate BP changes in healthy adult volunteers in three consecutive visits. BP was measured by a verified BP monitor simultaneously with iPTT registration at three exercise points: rest, exercise peak, and recovery. iPPG was simultaneously registered at two body locations during the exercise using high speed camera at 420 frames per second. iPTT was calculated as a time lag between pulse waves obtained as two iPPG’s registered from simultaneous recoding of head and palm areas. The average inter-person correlation between PTT and iPTT was 0.85 ± 0.08. The range of inter-person correlations between PTT and iPTT was from 0.70 to 0.95 (p < 0.05). The average inter-person coefficient of correlation between SBP and iPTT was -0.80 ± 0.12. The range of correlations between systolic BP and iPTT was from 0.632 to 0.960 with p < 0.05 for most of the participants. Preliminary data indicated that a high speed camera can be potentially utilized for unobtrusive contactless monitoring of abrupt blood pressure changes in a variety of settings. The initial prototype system was able to successfully generate approximation of pulse transit time and showed high intra-individual correlation between iPTT and BP. Further investigation of the proposed approach is warranted.
A novel method (Sophia) is presented to track oxygen saturation changes in a controlled environment using an RGB camera placed approximately 1.5 m away from the subject. The method is evaluated on five healthy volunteers (Fitzpatrick skin phenotypes II, III, and IV) whose oxygen saturations were varied between 80% and 100% in a purpose-built chamber over 40 minutes each. The method carefully selects regions of interest (ROI) in the camera image by calculating signal-to-noise ratios for each ROI. This allows it to track changes in oxygen saturation accurately with respect to a conventional pulse oximeter (median coefficient of determination, 0.85).
Early detection of secondary events is a major target of neuromonitoring in critically ill patients. Intracranial pressure (ICP) and cerebral perfusion pressure are the most widely accepted neuromonitoring parameters. Many studies have shown both to be related to mortality after traumatic brain injury. However, the benefit of ICP monitoring has not been established by a randomized controlled trial, and the efficacy of ICP‑guided management has indeed been challenged.
This review considers current neuromonitoring techniques in critical care medicine.
Asymmetrical changes in blood perfusion and asynchronous blood supply to head tissues likely contribute to migraine pathophysiology. Imaging was widely used in order to understand hemodynamic variations in migraine. However, mapping of blood pulsations in the face of migraineurs has not been performed so far. We used the Blood Pulsation Imaging (BPI) technique, which was recently developed in our group, to establish whether 2D-imaging of blood pulsations parameters can reveal new biomarkers of migraine. BPI characteristics were measured in migraineurs during the attack-free interval and compared to healthy subjects with and without a family history of migraine. We found a novel phenomenon of transverse waves of facial blood perfusion in migraineurs in contrast to healthy subjects who showed synchronous blood delivery to both sides of the face. Moreover, the amplitude of blood pulsations was symmetrically distributed over the face of healthy subjects, but asymmetrically in migraineurs and subjects with a family history of migraine. In the migraine patients we found a remarkable correlation between the side of unilateral headache and the direction of the blood perfusion wave. Our data suggest that migraine is associated with lateralization of blood perfusion and asynchronous blood pulsations in the facial area, which could be due to essential dysfunction of the autonomic vascular control in the face. These findings may further enhance our understanding of migraine pathophysiology and suggest new easily available biomarkers of this pathology.
Nurses have traditionally relied on five vital signs to assess their patients: temperature, pulse, blood pressure, respiratory rate and oxygen saturation. However, as patients hospitalised today are sicker than in the past, these vital signs may not be adequate to identify those who are clinically deteriorating. This paper describes clinical issues to consider when measuring vital signs as well as proposing additional assessments of pain, level of consciousness and urine output, as part of routine patient assessment.
Objective:
Photoplethysmography imaging (PPGI) has gained immense attention over the last few years but only a few works have addressed morphological analysis so far. Pulse wave decomposition (PWD), i.e. the decomposition of a pulse wave by a varying number of kernels, allows for such analyses. This work investigates the applicability of PWD algorithms in the context of PPGI.
Approach:
We used simulated and experimental data to compare various PWD algorithms from the literature regarding their robustness against noise and motion artifacts while preserving morphological information as well as regarding their ability to reveal physiological changes by PPGI.
Main results:
Our experiments prove that algorithms that combine Gamma and Gaussian distributions outperform other choices. Further, algorithms with two kernels exhibit the highest robustness against noise and motion artifacts (improvement in [Formula: see text] of 14.09 %) while preserving the morphology similarly to algorithms using more kernels. Lastly, we showed that PWD can reveal physiological changes upon distal stimuli by PPGI.
Significance:
This work proves the feasibility of pulse decomposition analysis in PPGI, particularly for algorithms with a low number of kernels, and opens up novel applications for PPGI. Not only for PPGI but for future research on PWD in general, our findings have importance as they elucidate differences between PWD algorithms and emphasize the importance of using initial values. To support such future research, we have released the algorithms and simulated data to the public.
Continuous monitoring of respiratory activity is desirable in many clinical applications to detect respiratory events. Non-contact monitoring of respiration can be achieved with near- and far-infrared spectrum cameras. However, current technologies are not sufficiently robust to be used in clinical applications. For example, they fail to estimate an accurate respiratory rate (RR) during apnea. We present a novel algorithm based on multispectral data fusion that aims at estimating RR also during apnea. The algorithm independently addresses the RR estimation and apnea detection tasks. Respiratory information is extracted from multiple sources and fed into an RR estimator and an apnea detector whose results are fused into a final respiratory activity estimation. We evaluated the system retrospectively using data from 30 healthy adults who performed diverse controlled breathing tasks while lying supine in a dark room and reproduced central and obstructive apneic events. Combining multiple respiratory information from multispectral cameras improved the root mean square error (RMSE) accuracy of the RR estimation from up to 4.64 monospectral data down to 1.60 breaths/min. The median F1 scores for classifying obstructive (0.75 to 0.86) and central apnea (0.75 to 0.93) also improved. Furthermore, the independent consideration of apnea detection led to a more robust system (RMSE of 4.44 vs. 7.96 breaths/min). Our findings may represent a step towards the use of cameras for vital sign monitoring in medical applications.
Pain sensation is essential for survival, since it draws attention to physical threat to the body. Pain assessment is usually done through self-reports. However, self-assessment of pain is not available in the case of noncommunicative patients, and therefore, observer reports should be relied upon. Observer reports of pain could be prone to errors due to subjective biases of observers. Moreover, continuous monitoring by humans is impractical. Therefore, automatic pain detection technology could be deployed to assist human caregivers and complement their service, thereby improving the quality of pain management, especially for noncommunicative patients. Facial expressions are a reliable indicator of pain, and are used in all observer-based pain assessment tools. Following the advancements in automatic facial expression analysis, computer vision researchers have tried to use this technology for developing approaches for automatically detecting pain from facial expressions. This paper surveys the literature published in this field over the past decade, categorizes it, and identifies future research directions. The survey covers the pain datasets used in the reviewed literature, the learning tasks targeted by the approaches, the features extracted from images and image sequences to represent pain-related information, and finally, the machine learning methods used.
Imaging photoplethysmography (iPPG) is an interesting alternative to laser speckle contrast imaging for the analysis of spatio-temporal patterns in the cutaneous microcirculation. Recent years have witnessed the development of sophisticated techniques for the non-invasive extraction of vascular-related features. These techniques, referred to as pulse decomposition algorithms (PDA), most often involve the analysis of photoplethysmographic waves. This study validated the use of a multi-Gaussian (PDA) for the automatic mapping of iPPG pulse waveforms acquired with a standard camera. We show that iPPG-based PDA can reveal differences in skin perfusion in response to cold stimuli. The study thus proves the potential for morphological analyses of the iPPG pulse waveform.
In present pilot study application of multi-spectral imaging photoplethysmography for assessment of chronic pain patients during topical skin heating test was proposed. Photoplethysmography signal was recorded at 420nm, 530nm and 810nm illumination from the skin and corresponding perfusion indexes and perfusion maps were calculated. The novel parameter-PPGflare index was introduced and compared in neuropathic patients and healthy volunteers. Preliminary results suggest that neuropathic patients exhibited significantly lower PPGflare index, and that local heating substantially change PPG waveform at heat exposed skin region. Present study emphasizes advantages of imaging photoplethysmography as a simple and cost-effective alternative to Laser Doppler with promising clinical potential in assessment of neuropathic patients. In this respect, we believe that our study adds novel information to the field of existing chronic pain diagnostics.
Purpose:
Camera-based photoplethysmography (cbPPG) remotely detects the volume pulse of cardiac ejection in the peripheral circulation. The cbPPG signal is sourced from the cutaneous microcirculation, yields a two-dimensional intensity map and is therefore an interesting monitoring technique. In this study we investigated, whether cbPPG is in general sufficiently sensitive to discern hemodynamic conditions.
Methods:
cbPPG recordings of seventy patients recovering from cardiac surgery were analyzed. Photoplethysmograms were processed offline and the optical pulse power (OPP) of cardiac ejection was calculated. Hemodynamic data, image intensity and patient movements were recorded synchronously. The effects of hemodynamic parameters and measurement conditions on the patient's individual OPP variability and their actual OPP values were calculated in mixed-effects regression models.
Results:
Mean arterial pressure, pulse pressure, heart rate and central venous pressure significantly explained the individual OPP variability. Pulse pressure had the highest explanatory power (19.9%). Averaged OPP significantly increased with pulse pressure and mean arterial pressure (p < 0.001, respectively) and decreased with higher heart rate (p = 0.024). Central venous pressure had a two-directional, non-significant effect on averaged OPP. Image intensity and patient movements did significantly affect OPP. After adjustment for hemodynamic co-variables and measurement conditions, the effect of pulse pressure and heart rate remained unchanged, whereas that of mean arterial pressure vanished.
Conclusion:
cbPPG is sensitive to hemodynamic parameters in critical care patients. It is a potential application for monitoring the peripheral circulation. Its value in a clinical setting has to be determined.
Background:
Large amounts of patient data are routinely manually collected in hospitals by using standalone medical devices, including vital signs. Such data is sometimes stored in spreadsheets, not forming part of patients' electronic health records, and is therefore difficult for caregivers to combine and analyze. One possible solution to overcome these limitations is the interconnection of medical devices via the Internet using a distributed platform, namely the Internet of Things. This approach allows data from different sources to be combined in order to better diagnose patient health status and identify possible anticipatory actions.
Methods:
This work introduces the concept of the Internet of Health Things (IoHT), focusing on surveying the different approaches that could be applied to gather and combine data on vital signs in hospitals. Common heuristic approaches are considered, such as weighted early warning scoring systems, and the possibility of employing intelligent algorithms is analyzed.
Results:
As a result, this article proposes possible directions for combining patient data in hospital wards to improve efficiency, allow the optimization of resources, and minimize patient health deterioration.
Conclusion:
It is concluded that a patient-centered approach is critical, and that the IoHT paradigm will continue to provide more optimal solutions for patient management in hospital wards.
We present an imaging-based method for noncontact spirometry. The method tracks the subtle respiratory-induced shoulder movement of a subject, builds a calibration curve, and determines the flow-volume spirometry curve and vital respiratory parameters, including forced expiratory volume in the first second, forced vital capacity, and peak expiratory flow rate. We validate the accuracy of the method by comparing the data with those simultaneously recorded with a gold standard reference method and examine the reliability of the noncontact spirometry with a pilot study including 16 subjects. This work demonstrates that the noncontact method can provide accurate and reliable spirometry tests with a webcam. Compared to the traditional spirometers, the present noncontact spirometry does not require using a spirometer, breathing into a mouthpiece, or wearing a nose clip, thus making spirometry test more easily accessible for the growing population of asthma and chronic obstructive pulmonary diseases. © 2017 Society of Photo-Optical Instrumentation Engineers (SPIE).
Over recent years there has been an increase in the implementation of goal-directed therapy using minimally invasive haemodynamic monitoring techniques to guide peri-operative care. Since the introduction of the pulmonary artery flotation catheter in the 1980s, various haemodynamic monitors have been developed, each associated with their own benefits and limitations. Goal-directed therapy has been well-established as a standard of care in the peri-operative period and has largely been associated with a reduction in morbidity and mortality. However, evidence over the last few years from major studies has led us to question: what is the future for goal-directed therapy? Care of the peri-operative patient has significantly evolved over the last decade and this needs to be taken into account when assessing the results of these studies. We should therefore not look at the effects of goal-directed therapy in isolation but as part of a progressive care bundle. Additionally, other markers of haemodynamic status have also begun to be further appreciated and these are worthy of further investigation. We feel that the future for haemodynamic monitoring remains promising with new areas of interest continuously emerging, but further research is still required. © 2017 The Association of Anaesthetists of Great Britain and Ireland
Vital parameter monitoring of term and preterm infants during incubator care with self-adhesive electrodes or sensors directly positioned on the skin [e.g. photoplethysmography (PPG) for oxygen saturation or electrocardiography (ECG)] is an essential part of daily routine care in neonatal intensive care units. For various reasons, this kind of monitoring contains a lot of stress for the infants. Therefore, there is a need to measure vital parameters (for instance respiration, temperature, pulse, oxygen saturation) without mechanical or conductive contact. As a non-contact method of monitoring, we present an adapted version of camera-based photoplethysmography imaging (PPGI) according to neonatal requirements. Similar to classic PPG, the PPGI camera detects small temporal changes in the term and preterm infant’s skin brightness due to the cardiovascular rhythm of dermal blood perfusion. We involved 10 preterm infants in a feasibility study [five males and five females; mean gestational age: 26 weeks (24–28 weeks); mean biological age: 35 days (8–41 days); mean weight at the time of investigation: 960 g (670–1290 g)]. The PPGI camera was placed directly above the incubators with the infant inside illuminated by an infrared light emitting diode (LED) array (850 nm). From each preterm infant, 5-min video sequences were recorded and analyzed post hoc. As the measurement scenario was kept as realistic as possible, the infants were not constrained in their movements in front of the camera. Movement intensities were assigned into five classes (1: no visible motion to 5: heavy struggling). PPGI was found to be significantly sensitive to movement artifacts. However, for movement classes 1–4, changes in blood perfusion according to the heart rate (HR) were recovered successfully (Pearson correlation: r=0.9759; r=0.765 if class 5 is included). The study was approved by the Ethics Committee of the Universal Hospital of the RWTH Aachen University, Aachen, Germany (EK 254/13).
Burn excision, a difficult technique owing to the training required to identify the extent and depth of injury, will benefit from a tool that can queue the surgeon as to where and how much to resect. We explored two rapid and noninvasive optical imaging techniques in their ability to identify burn tissue from the viable wound bed during an animal model of tangential burn excision. Photoplethysmography (PPG) imaging and multispectral imaging (MSI) were used to image the initial, intermediate, and final stages of burn excision of a deep partial-thickness burn. PPG imaging maps blood flow in the skin's microcirculation, and MSI collects the tissue reflectance spectrum in visible and infrared wavelengths of light to classify tissue based on a reference library. A porcine deep partial-thickness burn model was generated and serial tangential excision accomplished with an electric dermatome set to 1.0 mm depth. Excised eschar was stained with hematoxylin and eosin to determine the extent of burn remaining at each excision depth. We confirmed that the PPG imaging device showed significantly less blood flow where burn tissue was present, and the MSI method could delineate burn tissue in the wound bed from the viable wound bed. These results were confirmed independently by a histological analysis. We found these devices can identify the proper depth of excision, and their images could queue a surgeon as to the preparedness of the wound bed for grafting. These image outputs are expected to facilitate clinical judgment in the operating room.
We propose a technique for non-contact imaging of venous compliance that uses the red, green, and blue (RGB) camera. Any change in blood concentration is estimated from an RGB image of the skin, and a regression formula is calculated from that change. Venous compliance is obtained from a differential form of the regression formula. In vivo experiments with human subjects confirmed that the proposed method does differentiate the venous compliances among individuals. In addition, the image of venous compliance is obtained by performing the above procedures for each pixel. Thus, we can measure venous compliance without physical contact with sensors and, from the resulting images, observe the spatial distribution of venous compliance, which correlates with the distribution of veins.
Evidence exists that the secondary insults of reduced cerebral perfusion and oxygenation are directly correlated with poor neurological outcomes, particularly after traumatic brain injury (TBI) and subarachnoid haemorrhage (SAH).There are several advanced neurological monitoring modalities available, some in routine use and others still research tools which can measure global and regional variables including pressure, flow, oxygenation and the concentration of metabolites.Close monitoring of traditional systemic variables combined with advance neurological monitoring can provide early detection of secondary insults and allow early goal directed interventions to improve outcomes.
Camera-based photoplethysmography provides a mean to monitor cardiovascular parameters remotely. This contribution tackles heart beat detection from remote photoplethysmograms (rPPG) by using a Wavelet-based detection algorithm and time delay estimation. Using experimental recordings of 18 healthy volunteers under resting conditions we demonstrate that depending on the used region of interest detection accuracies of 95% to 99% can be obtained. Time delay estimation is shown to improve the temporal exactness of the detections. Future work will be directed at the detection in non-resting periods and the automated identification of usable signal segments.
This paper presents the experimental setup and preliminary results of a near infrared CCD camera based Photoplethysmography Imaging (PPGI) system, which has been shown to be suitable for contactless and spatially resolved assessment of rhythmical blood volume changes in the skin. To visualize the complex rhythmical patterns in the dermal perfusion the Wavelet Transform is utilized. It is able to jointly assess time and frequency behavior of signals and thus allows to analyze instationary oscillations and variabilities in the different human rhythmics. The presented system is expected to provide new insights into the functional sequences of physiological tissue perfusion as well as of the perfusion status in ulcer formation and wound healing.
BJECTIVE: Rapid response team activation criteria were created using expert opinion and have demonstrated variable accuracy in previous studies. We developed a cardiac arrest risk triage score to predict cardiac arrest and compared it to the Modified Early Warning Score, a commonly cited rapid response team activation criterion.
A retrospective cohort study.
An academic medical center in the United States.
All patients hospitalized from November 2008 to January 2011 who had documented ward vital signs were included in the study. These patients were divided into three cohorts: patients who suffered a cardiac arrest on the wards, patients who had a ward to intensive care unit transfer, and patients who had neither of these outcomes (controls).
None.
Ward vital signs from admission until discharge, intensive care unit transfer, or ward cardiac arrest were extracted from the medical record. Multivariate logistic regression was used to predict cardiac arrest, and the cardiac arrest risk triage score was calculated using the regression coefficients. The model was validated by comparing its accuracy for detecting intensive care unit transfer to the Modified Early Warning Score. Each patient's maximum score prior to cardiac arrest, intensive care unit transfer, or discharge was used to compare the areas under the receiver operating characteristic curves between the two models. Eighty-eight cardiac arrest patients, 2,820 intensive care unit transfers, and 44,519 controls were included in the study. The cardiac arrest risk triage score more accurately predicted cardiac arrest than the Modified Early Warning Score (area under the receiver operating characteristic curve 0.84 vs. 0.76; p = .001). At a specificity of 89.9%, the cardiac arrest risk triage score had a sensitivity of 53.4% compared to 47.7% for the Modified Early Warning Score. The cardiac arrest risk triage score also predicted intensive care unit transfer better than the Modified Early Warning Score (area under the receiver operating characteristic curve 0.71 vs. 0.67; p < .001).
The cardiac arrest risk triage score is simpler and more accurately detected cardiac arrest and intensive care unit transfer than the Modified Early Warning Score. Implementation of this tool may decrease rapid response team resource utilization and provide a better opportunity to improve patient outcomes than the modified early warning score.