Video plethysmography for contactless blood pressure and heart rate measurement in perioperative care

The purpose of this study was to evaluate the feasibility and accuracy of remote Video Plethysmography (VPPG) for contactless measurements of blood pressure (BP) and heart rate (HR) in adult surgical patients in a hospital setting. An iPad Pro was used to record a 1.5-minute facial video of the participant's face and VPPG was used to extract vital signs measurements. A standard medical device (Welch Allyn) was used for comparison to measure BP and HR. Trial registration: NCT05165381. Two-hundred-sixteen participants consented and completed the contactless BP and HR monitoring (mean age 54.1 ± 16.8 years, 58% male). The consent rate was 75% and VPPG was 99% successful in capturing BP and HR. VPPG predicted SBP, DBP, and HR with a measurement bias ± SD, -8.18 ± 16.44 mmHg, - 6.65 ± 9.59 mmHg, 0.09 ± 6.47 beats/min respectively. Pearson's correlation for all measurements between VPPG and standard medical device was significant. Correlation for SBP was moderate (0.48), DBP was weak (0.29), and HR was strong (0.85). Most patients were satisfied with the non-contact technology with an average rating of 8.7/10 and would recommend it for clinical use. VPPG was highly accurate in measuring HR, and is currently not accurate in measuring BP in surgical patients. The VPPG BP algorithm showed limitations in capturing individual variations in blood pressure, highlighting the need for further improvements to render it clinically effective across all ranges. Contactless vital signs monitoring was well-received and earned a high satisfaction score.

Non-contact heart rate estimation based on singular spectrum component reconstruction using low-rank matrix and autocorrelation

The remote photoplethysmography (rPPG) based on cameras, a technology for extracting pulse wave from videos, has been proved to be an effective heart rate (HR) monitoring method and has great potential in many fields; such as health monitoring. However, the change of facial color intensity caused by cardiovascular activities is weak. Environmental illumination changes and subjects' facial movements will produce irregular noise in rPPG signals, resulting in distortion of heart rate pulse signals and affecting the accuracy of heart rate measurement. Given the irregular noises such as motion artifacts and illumination changes in rPPG signals, this paper proposed a new method named LA-SSA. It combines low-rank sparse matrix decomposition and autocorrelation function with singular spectrum analysis (SSA). The low-rank sparse matrix decomposition is employed to globally optimize the components of the rPPG signal obtained by SSA, and some irregular noise is removed. Then, the autocorrelation function is used to optimize the global optimization results locally. The periodic components related to the heartbeat signal are selected, and the denoised rPPG signal is obtained by weighted reconstruction with a singular value ratio. The experiment using UBFC-RPPG and PURE database is performed to assess the performance of the method proposed in this paper. The average absolute error was 1.37 bpm, the 95% confidence interval was -7.56 bpm to 6.45 bpm, and the Pearson correlation coefficient was 98%, superior to most existing video-based heart rate extraction methods. Experimental results show that the proposed method can estimate HR effectively.

Skin tissue perfusion mapping triggered by an audio-(de)modulated reference signal

Spatial mapping of skin perfusion provides essential information about physiological processes that are often hidden from the eyes of the examining physician. The perfusion map quality depends on several key factors, such as the camera system type, frame rate, sensitivity, or signal-to-noise ratio. When investigating physiological parameters, the reference signal allows for increasing the spatial resolution of the photoplethysmography imaging (PPGI) system. On the other hand, it increases the system complexity and the synchronization prerequisites. Our solution is a hardware device that modulates the reference biosignal into the audio frequency band. This signal is connected to the mic input of a digital camera or a smartphone, enabling the transformation of such a device into a PPGI measurement system even in the case of compressed video recording using lock-in amplification technique. It also brings the possibility of synchronous recording of PPGI and another reference signal such as conventional photoplethysmogram or electrocardiogram.

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.

Multi-ROI Spectral Approach for the Continuous Remote Cardio-Respiratory Monitoring from Mobile Device Built-In Cameras

Heart rate (HR) and respiratory rate (f_R) can be estimated by processing videos framing the upper body and face regions without any physical contact with the subject. This paper proposed a technique for continuously monitoring HR and f_R via a multi-ROI approach based on the spectral analysis of RGB video frames recorded with a mobile device (i.e., a smartphone's camera). The respiratory signal was estimated by the motion of the chest, whereas the cardiac signal was retrieved from the pulsatile activity at the level of right and left cheeks and forehead. Videos were recorded from 18 healthy volunteers in four sessions with different user-camera distances (i.e., 0.5 m and 1.0 m) and illumination conditions (i.e., natural and artificial light). For HR estimation, three approaches were investigated based on single or multi-ROI approaches. A commercially available multiparametric device was used to record reference respiratory signals and electrocardiogram (ECG). The results demonstrated that the multi-ROI approach outperforms the single-ROI approach providing temporal trends of both the vital parameters comparable to those provided by the reference, with a mean absolute error (MAE) consistently below 1 breaths·min^-1 for f_R in all the scenarios, and a MAE between 0.7 bpm and 6 bpm for HR estimation, whose values increase at higher distances.

Contactless Vital Signs Monitoring From Videos Recorded With Digital Cameras: An Overview

The measurement of physiological parameters is fundamental to assess the health status of an individual. The contactless monitoring of vital signs may provide benefits in various fields of application, from healthcare and clinical setting to occupational and sports scenarios. Recent research has been focused on the potentiality of camera-based systems working in the visible range (380-750 nm) for estimating vital signs by capturing subtle color changes or motions caused by physiological activities but invisible to human eyes. These quantities are typically extracted from videos framing some exposed body areas (e.g., face, torso, and hands) with adequate post-processing algorithms. In this review, we provided an overview of the physiological and technical aspects behind the estimation of vital signs like respiratory rate, heart rate, blood oxygen saturation, and blood pressure from digital images as well as the potential fields of application of these technologies. Per each vital sign, we provided the rationale for the measurement, a classification of the different techniques implemented for post-processing the original videos, and the main results obtained during various applications or in validation studies. The available evidence supports the premise of digital cameras as an unobtrusive and easy-to-use technology for physiological signs monitoring. Further research is needed to promote the advancements of the technology, allowing its application in a wide range of population and everyday life, fostering a biometrical holistic of the human body (BHOHB) approach.

Comparative study on the effect of color spaces and color formats on heart rate measurement using the imaging photoplethysmography (IPPG) method

BACKGROUND:

The imaging photoplethysmography (IPPG) technology has been demonstrated to be an effective method for heart rate (HR) monitoring. However, some interference caused by the ambient illumination variation and facial motion severely influences the accuracy of the HR measurement. Some color spaces and color formats are assumed to reduce the interference, and enhance the accuracy of HR estimation.

OBJECTIVE:

The aim is to identify the optimal color space and format for IPPG based HR measurement.

METHODS:

Six color spaces and 3 color formats are compared in this study, based on an IPPG based HR measurement system. 424 pieces of videos captured by the system are used for the selection of the optimal color channel and color space; while 10 pieces of videos are for the identification of the optimal color format.

RESULTS:

The results shows that the green channel of RGB space is the optimal color channel, and RGB is the optimal color space, in respect of the mean squared error of HR estimation. BayerBG 8bit is found to be the optimal color format for video recording, which can significantly reduce the HR estimation error.

CONCLUSIONS:

BayerBG 8bit color format for video recording, and RGB color space for video analysis is suggested for the IPPG based HR measurement system. The suitable configuration of color space and format could enhance the accuracy of HR measurement.

Contactless heart rate measurement in newborn infants using a multimodal 3D camera system

Newborns and preterm infants require accurate and continuous monitoring of their vital parameters. Contact-based methods of monitoring have several disadvantages, thus, contactless systems have increasingly attracted the neonatal communities' attention. Camera-based photoplethysmography is an emerging method of contactless heart rate monitoring. We conducted a pilot study in 42 healthy newborn and near-term preterm infants for assessing the feasibility and accuracy of a multimodal 3D camera system on heart rates (HR) in beats per min (bpm) compared to conventional pulse oximetry. Simultaneously, we compared the accuracy of 2D and 3D vision on HR measurements. The mean difference in HR between pulse oximetry and 2D-technique added up to + 3.0 bpm [CI-3.7 - 9.7; p = 0.359, limits of agreement (LOA) ± 36.6]. In contrast, 3D-technique represented a mean difference in HR of + 8.6 bpm (CI 2.0-14.9; p = 0.010, LOA ± 44.7) compared to pulse oximetry HR. Both, intra- and interindividual variance of patient characteristics could be eliminated as a source for the results and the measuring accuracy achieved. Additionally, we proved the feasibility of this emerging method. Camera-based photoplethysmography seems to be a promising approach for HR measurement of newborns with adequate precision; however, further research is warranted.

Smartphones and Video Cameras: Future Methods for Blood Pressure Measurement

Regular blood pressure (BP) monitoring enables earlier detection of hypertension and reduces cardiovascular disease. Cuff-based BP measurements require equipment that is inconvenient for some individuals and deters regular home-based monitoring. Since smartphones contain sensors such as video cameras that detect arterial pulsations, they could also be used to assess cardiovascular health. Researchers have developed a variety of image processing and machine learning techniques for predicting BP via smartphone or video camera. This review highlights research behind smartphone and video camera methods for measuring BP. These methods may in future be used at home or in clinics, but must be tested over a larger range of BP and lighting conditions. The review concludes with a discussion of the advantages of the various techniques, their potential clinical applications, and future directions and challenges. Video cameras may potentially measure multiple cardiovascular metrics including and beyond BP, reducing the risk of cardiovascular disease.

Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis

The objective of this systematic review and meta-analysis was to analyze the effectiveness of contactless vital sign monitors that utilize a consumer-friendly camera versus medical grade instruments. A multiple database search was conducted from inception to September 2020. Inclusion criteria were as follows: studies that used a consumer-grade camera (smartphone/webcam) to examine contactless vital signs in adults; evaluated the non-contact device against a reference medical device; and used the participants’ face for measurement. Twenty-six studies were included in the review of which 16 were included in Pearson’s correlation and 14 studies were included in the Bland–Altman meta-analysis. Twenty-two studies measured heart rate (HR) (92%), three measured blood pressure (BP) (12%), and respiratory rate (RR) (12%). No study examined blood oxygen saturation (SpO₂). Most studies had a small sample size (≤ 30 participants) and were performed in a laboratory setting. Our meta-analysis found that consumer-grade contactless vital sign monitors were accurate in comparison to a medical device in measuring HR. Current contactless monitors have limitations such as motion, poor lighting, and lack of automatic face tracking. Currently available consumer-friendly contactless monitors measure HR accurately compared to standard medical devices. More studies are needed to assess the accuracy of contactless BP and RR monitors. Implementation of contactless vital sign monitors for clinical use will require validation in a larger population, in a clinical setting, and expanded to encompass other vital signs including BP, RR, and SpO₂.

Remote heart rate monitoring - Assessment of the Facereader rPPg by Noldus

Remote photoplethysmography (rPPG) allows contactless monitoring of human cardiac activity through a video camera. In this study, we assessed the accuracy and precision for heart rate measurements of the only consumer product available on the market, namely the FacereaderTM rPPG by Noldus, with respect to a gold standard electrocardiograph. Twenty-four healthy participants were asked to sit in front of a computer screen and alternate two periods of rest with two stress tests (i.e. Go/No-Go task), while their heart rate was simultaneously acquired for 20 minutes using the ECG criterion measure and the FacereaderTM rPPG. Results show that the FacereaderTM rPPG tends to overestimate lower heart rates and underestimate higher heart rates compared to the ECG. The Facereader™ rPPG revealed a mean bias of 9.8 bpm, the 95% limits of agreement (LoA) ranged from almost -30 up to +50 bpm. These results suggest that whilst the rPPG FacereaderTM technology has potential for contactless heart rate monitoring, its predictions are inaccurate for higher heart rates, with unacceptable precision across the entire range, rendering its estimates unreliable for monitoring individuals.

Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions

BACKGROUND

Currently, many imaging photoplethysmography (IPPG) researches have reported non-contact measurements of physiological parameters, such as heart rate (HR), respiratory rate (RR), etc. However, it is accepted that only HR measurement has been mature for applications, and other estimations are relatively incapable for reliable applications. Thus, it is worth keeping on persistent studies. Besides, there are some issues commonly involved in these approaches need to be explored further. For example, motion artifact attenuation, an intractable problem, which is being attempted to be resolved by sophisticated video tracking and detection algorithms.

METHODS

This paper proposed a blind source separation-based method that could synchronously measure RR and HR in non-contact way. A dual region of interest on facial video image was selected to yield 6-channels Red/Green/Blue signals. By applying Second-Order Blind Identification algorithm to those signals generated above, we obtained 6-channels outputs that contain blood volume pulse (BVP) and respiratory motion artifact. We defined this motion artifact as respiratory signal (RS). For the automatic selections of the RS and BVP among these outputs, we devised a kurtosis-based identification strategy, which guarantees the dynamic RR and HR monitoring available.

RESULTS

The experimental results indicated that, the estimation by the proposed method has an impressive performance compared with the measurement of the commercial medical sensors.

CONCLUSIONS

The proposed method achieved dynamic measurement of RR and HR, and the extension and revision of it may have the potentials for more physiological signs detection, such as heart rate variability, eye blinking, nose wrinkling, yawn, as well as other muscular movements. Thus, it might provide a promising approach for IPPG-based applications such as emotion computation and fatigue detection, etc.

Camera-Based, Non-Contact, Vital-Signs Monitoring Technology May Provide a Way for the Early Prevention of SIDS in Infants

Sudden infant death syndrome (SIDS) is the unexplained death, usually during sleep, of a baby younger than 1-year-old. Even though researchers have discovered some factors that may put babies at extra risk, SIDS remains unpredictable up until now. One hypothesis is that impaired cardiovascular control may play a role in the underlying mechanism of SIDS. A reduction of heart rate variability (HRV) and progressive decrease in heart rate (HR) have been observed in infants who have later succumbed to SIDS. Many clues indicated the heart could be the final weakness in SIDS. Therefore, continuous monitoring of the dynamic changes within the heart may provide a possible preventive strategy of SIDS. Camera-based photoplethysmography was recently demonstrated as a contactless method to determine HR and HRV. This perspective presents a hypothesis that a camera-based, non-contact, vital-sign monitoring technology, which can indicate abnormal changes or a sudden loss of vital signs in a timely manner, may enable a crucial and low-cost means for the early prevention of SIDS in newborn infants.

Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging

Photoplethysmography (PPG) is a noninvasive optical technique for detecting microvascular blood volume changes in tissues. Its ease of use, low cost and convenience make it an attractive area of research in the biomedical and clinical communities. Nevertheless, its single spot monitoring and the need to apply a PPG sensor directly to the skin limit its practicality in situations such as perfusion mapping and healing assessments or when free movement is required. The introduction of fast digital cameras into clinical imaging monitoring and diagnosis systems, the desire to reduce the physical restrictions, and the possible new insights that might come from perfusion imaging and mapping inspired the evolution of the conventional PPG technology to imaging PPG (IPPG). IPPG is a noncontact method that can detect heart-generated pulse waves by means of peripheral blood perfusion measurements. Since its inception, IPPG has attracted significant public interest and provided opportunities to improve personal healthcare. This study presents an overview of the wide range of IPPG systems currently being introduced along with examples of their application in various physiological assessments. We believe that the widespread acceptance of IPPG is happening, and it will dramatically accelerate the promotion of this healthcare model in the near future.