Techniques for estimating blood pressure variation using video images

Deep learning and remote photoplethysmography powered advancements in contactless physiological measurement

In recent decades, there has been ongoing development in the application of computer vision (CV) in the medical field. As conventional contact-based physiological measurement techniques often restrict a patient's mobility in the clinical environment, the ability to achieve continuous, comfortable and convenient monitoring is thus a topic of interest to researchers. One type of CV application is remote imaging photoplethysmography (rPPG), which can predict vital signs using a video or image. While contactless physiological measurement techniques have an excellent application prospect, the lack of uniformity or standardization of contactless vital monitoring methods limits their application in remote healthcare/telehealth settings. Several methods have been developed to improve this limitation and solve the heterogeneity of video signals caused by movement, lighting, and equipment. The fundamental algorithms include traditional algorithms with optimization and developing deep learning (DL) algorithms. This article aims to provide an in-depth review of current Artificial Intelligence (AI) methods using CV and DL in contactless physiological measurement and a comprehensive summary of the latest development of contactless measurement techniques for skin perfusion, respiratory rate, blood oxygen saturation, heart rate, heart rate variability, and blood pressure.

Non-Contact Measurement of Blood Oxygen Saturation Using Facial Video Without Reference Values

The continuous measurement of percutaneous oxygen saturation (SpO2) enables diseases that cause hypoxemia to be detected early and patients' conditions to be monitored. Currently, SpO2 is mainly measured using a pulse oximeter, which, owing to its simplicity, can be used in clinical settings and at home. However, the pulse oximeter requires a sensor to be in contact with the skin; therefore, prolonged use of the pulse oximeter for neonates or patients with sensitive skin may cause local inflammation or stress due to restricted movement. In addition, owing to COVID-19, there has been a growing demand for the contactless measurement of SpO2. Several studies on measuring SpO2 without contact used skin video images have been conducted. However, in these studies, the SpO2 values were estimated using a linear regression model or a look-up table that required reference values obtained using a contact-type pulse oximeter. In this study, we propose a new technique for the contactless measurement of SpO2 that does not require reference values. Specifically, we used certain approaches that reduced the influence of non-pulsating components and utilized different light wavelengths of video images that penetrated subcutaneously to different depths. We experimentally investigated the accuracy of SpO2 measurements using the proposed methods. The results indicate that the proposed methods were more accurate than the conventional method.

Prediction and prevention system for Severe Acute Respiratory Syndrome CoronaVirus 2 infection by preempting the onset of a cough

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is fast becoming one of the most significant infections worldwide. Of all the causes of SARS-CoV-2 infection, airborne-droplet infection via coughing is the most common. Therefore, if predicting the onset of a cough and preventing infection were possible, it would have a globally positive impact. Here, we describe a new prediction and prevention system for SARS-CoV-2 infection. Usually, air is inhaled prior to coughing, and the cough, which contains droplets of the virus, then occurs during acute exhalation. Therefore, if we can predict the onset of a cough, we can prevent the spread of SARS-CoV-2. At Tohoku University, a diagnosis system for evaluating swallowing motions and peripheral circulation has already been developed, and our prediction system can be integrated into this system. Using three-dimensional human body imaging, we developed a prediction system for preempting the onset of a cough. If we can predict the onset a cough, we can prevent the spread of SARS-CoV-2 infection, by decreasing the shower of virally active airborne droplets. Here, we describe the newly developed prediction and prevention system for SARS-CoV-2 infection that preempts the onset of a cough.Clinical Relevance- If predicting the onset of a cough and preventing infection were possible, it would have a globally positive impact. Here, we describe the newly developed prediction and prevention system for SARS-CoV-2 infection.

Deep Learning-Based Non-Contact IPPG Signal Blood Pressure Measurement Research

In this paper, a multi-stage deep learning blood pressure prediction model based on imaging photoplethysmography (IPPG) signals is proposed to achieve accurate and convenient monitoring of human blood pressure. A camera-based non-contact human IPPG signal acquisition system is designed. The system can perform experimental acquisition under ambient light, effectively reducing the cost of non-contact pulse wave signal acquisition while simplifying the operation process. The first open-source dataset IPPG-BP for IPPG signal and blood pressure data is constructed by this system, and a multi-stage blood pressure estimation model combining a convolutional neural network and bidirectional gated recurrent neural network is designed. The results of the model conform to both BHS and AAMI international standards. Compared with other blood pressure estimation methods, the multi-stage model automatically extracts features through a deep learning network and combines different morphological features of diastolic and systolic waveforms, which reduces the workload while improving accuracy.

Contactless skin perfusion monitoring with video cameras: tracking pharmacological vasoconstriction and vasodilation using photoplethysmographic changes

Objectives.Clinical assessment of skin perfusion informs prognosis in critically ill patients. Video camera monitoring could provide an objective, continuous method to monitor skin perfusion. In this prospective, interventional study of healthy volunteers, we tested whether video camera-derived photoplethysmography imaging and colour measurements could detect drug-induced skin perfusion changes.Approach.We monitored the lower limbs of 30 volunteers using video cameras while administering phenylephrine (a vasoconstrictor) and glyceryl trinitrate (a vasodilator). We report relative pixel intensity changes from baseline, as absolute values are sensitive to environmental factors. The primary outcome was the pre- to peak- infusion green channel amplitude change in the pulsatile PPGi waveform component. Secondary outcomes were pre-to-peak changes in the photoplethysmographic imaging waveform baseline, skin colour hue and skin colour saturation.Main results.The 30 participants had a median age of 29 years (IQR 25-34), sixteen (53%) were male. A 34.7% (p= 0.0001) mean decrease in the amplitude of the pulsatile photoplethysmographic imaging waveform occurred following phenylephrine infusion. A 30.7% (p= 0.000004) mean increase occurred following glyceryl trinitrate infusion. The photoplethysmographic imaging baseline decreased with phenylephrine by 2.1% (p= 0.000 02) and increased with glyceryl trinitrate by 0.5% (p= 0.026). Skin colour hue changed in opposite direction with phenylephrine (-0.0013,p= 0.0002) and glyceryl trinitrate (+0.0006,p= 0.019). Skin colour saturation decreased with phenylephrine by 0.0022 (p= 0.0002), with no significant change observed with glyceryl trinitrate (+0.0005,p= 0.21).Significance.Drug-induced vasoconstriction and vasodilation are associated with detectable changes in photoplethysmographic imaging waveform parameters and skin hue. Our findings suggest video cameras have great potential for continuous, contactless skin perfusion monitoring.

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.

Recent advances in selective photothermal therapy of tumor

Photothermal therapy (PTT), which converts light energy to heat energy, has become a new research hotspot in cancer treatment. Although researchers have investigated various ways to improve the efficiency of tumor heat ablation to treat cancer, PTT may cause severe damage to normal tissue due to the systemic distribution of photothermal agents (PTAs) in the body and inaccurate laser exposure during treatment. To further improve the survival rate of cancer patients and reduce possible side effects on other parts of the body, it is still necessary to explore PTAs with high selectivity and precise treatment. In this review, we summarized strategies to improve the treatment selectivity of PTT, such as increasing the accumulation of PTAs at tumor sites and endowing PTAs with a self-regulating photothermal conversion function. The views and challenges of selective PTT were discussed, especially the prospects and challenges of their clinical applications.

Recent Advances in Atherosclerotic Disease Screening Using Pervasive Healthcare

Atherosclerosis screening helps the medical model transform from therapeutic medicine to preventive medicine by assessing degree of atherosclerosis prior to the occurrence of fatal vascular events. Pervasive screening emphasizes atherosclerotic monitoring with easy access, quick process, and advanced computing. In this work, we introduced five cutting-edge pervasive technologies including imaging photoplethysmography (iPPG), laser Doppler, radio frequency (RF), thermal imaging (TI), optical fiber sensing and piezoelectric sensor. IPPG measures physiological parameters by using video images that record the subtle skin color changes consistent with cardiac-synchronous blood volume changes in subcutaneous arteries and capillaries. Laser Doppler obtained the information on blood flow by analyzing the spectral components of backscattered light from the illuminated tissues surface. RF is based on Doppler shift caused by the periodic movement of the chest wall induced by respiration and heartbeat. TI measures vital signs by detecting electromagnetic radiation emitted by blood flow. The working principle of optical fiber sensor is to detect the change of light properties caused by the interaction between the measured physiological parameter and the entering light. Piezoelectric sensors are based on the piezoelectric effect of dielectrics. All these pervasive technologies are noninvasive, mobile, and can detect physiological parameters related to atherosclerosis screening.

Comparison of Visible and Infrared Video Plethysmography Captured from Different Regions of the Human Face

Recently, video plethysmography (VPG) - a heart rate estimation technique using a video camera - has gained significant attention. Most studies of VPG have used a visible RGB camera; only a limited number of studies investigating near-infrared light (wavelength 750-2500 nm), which can be used even in a dark environment, have been performed. The purpose of this study was to investigate the differences between VPG data collected using visible light (VPG_VIS) or near-infrared light (VPG_NIR) from four facial areas (forehead, right cheek, left cheek, and nose). An experiment was conducted to obtain both VPG_VIS and VPG_NIR simultaneously by alternately irradiating the face with NIR and VIS lights. Experimental results showed that the root mean squared error of heart rate estimated using VPG_NIR was 1 bpm higher than that of VPG_VIS. However, contrary to our expectations, the power of the heartbeat-related component included in VPG_NIR was not reduced despite the absorbance of hemoglobin in the NIR light range being 1/100 of that in the VIS light range. This result supports the hypothesis that a main factor in the generation of VPG waves was change in the optical properties caused by blood vessels compressing the subcutaneous tissue and the venous bed. Additionally, the accuracy of the heart rate estimation using VPG tended to be high when the nose was set as the ROI. This result was likely associated with the anatomical structure of the nose.

Evaluation of the Pulse wave in the face for the patients with rotary blood pump (RP) in the Outpatient clinic

Rotary blood pump (RP) is one of the most important devices in the treatment of profound heart failure and is known to reduce the pulse in the blood pressure waveform, especially when it is used for axial flow. In an outpatient clinic, checking the pulse of a patient implanted with an RP can help diagnose the patient's condition. For that purpose, animal experiments with healthy adult goats implanted with the EVAHEART system were carried out after obtaining ethical committee approval. Visual imaging of the goats' faces was recorded using a video camera. The pulse waves were clearly recorded using the newly developed pulse diagnosis system with video imaging and compared with laser Doppler flowmeter and time series data. Spectral analysis of the time series data showed the usefulness of video imaging from outside the body. Clinical applications are planned, and this newly developed method is expected to be a useful diagnostic method for evaluating the cardiac function in patients implanted with RPs in the future.

Noncontact Blood Pressure Monitoring Technology using Facial Photoplethysmograms

We propose noncontact blood pressure estimation technology using photoplethysmograms (PPGs) extracted from camera images of only user's face and this estimation can be realized without calibration, which usually needs to be performed for each individual. Proposed technology contains the pulse wave detection method robust to lighting conditions. The influence of users' body motions was evaluated by our experimental system. We also propose the method to reduce the blood pressure prediction error by classifying users according to their vascular conditions which can be detected from facial PPGs.

Estimation of Absolute Blood Pressure Using Video Images Captured at Different Heights from the Heart

The risk of cardiovascular diseases is related to the absolute level of blood pressure as well as its fluctuation while sleeping or during daily activities. To assess the risk, a simpler method to monitor daily blood pressure is desirable. In recent years, there has been a focus on developing a method to obtain pulse waves from video images of the human body. This is a promising technique to acquire biometric information without contact. In this study, we propose a new method to estimate the absolute level of blood pressure by using two video images of human hands captured at different heights from the heart. We focus on the amplitude difference of pulse waves obtained from the video images and derive an equation to estimate blood pressure based on the relationship between the internal pressure and the cross-sectional area of the blood vessel. The accuracy of the estimation was evaluated using data obtained from 5 healthy subjects performing cycling exercises that change their blood pressure. The average value of the root mean square error between the real value and the estimated value was 25.7 mmHg, while that of correlation coefficient was 0.66. There were large individual differences, particularly in the estimation of the absolute value of blood pressure. This result suggests the need for individual correction of the compliance curve, which represents the relationship between the internal pressure and the cross-sectional area of the blood vessel.

Low-frequency facial hemodynamic oscillations distinguish migraineurs from non-headache controls

Background

Surface imaging is a promising, noninvasive approach to assess regional perfusion in craniovascular disorders such as migraine.

Methods

We used optical imaging to examine differences in facial blood volume at baseline and in response to ammonia inhalation (a noxious stimulus), as well as standardized measures of cardiovascular autonomic function, in healthy, non-headache controls (n = 43) and in interictal migraine subjects (n = 22).

Results

Resting facial cutaneous oscillation (FCO) frequency was significantly different in migraine compared to healthy controls. Following ammonia inhalation, healthy controls showed a significant increase in resting FCO frequency, whereas this response was not significant in the migraine group. Standardized autonomic reflex parameters did not differ significantly between study groups, and facial cutaneous activity did not correlate with standardized cardiovascular autonomic reflex parameters, suggesting potentially different regulation.

Conclusions

This approach to the assessment of craniofacial hemodynamic function appears to exhibit differing mechanisms from previously available techniques, and represents a promising new physiological biomarker for the study of craniofacial vascular function in migraine and potentially other craniovascular disorders.

Noise Reduction Technique for Single-Color Video Plethysmography Using Singular Spectrum Analysis

Recently, a contactless method for measuring a biological signal using a video camera has garnered attention. Especially, video plethysmography, a technique for obtaining a pulse wave from a video, is useful for managing the health of people on a daily basis. However, any body movement of a person subjected to the measurement leads to the generation of irregular noise in video plethysmography and reduces the accuracy of the recorded biological information, e.g., heart rate, during the measurement. Blind source separation is a popular technique for eliminating noise from the results of video plethysmography comprising different multiple-color channels. However, it is difficult to apply this technique to a single-color video such as a near-infrared video. Herein, a new method that combines singular spectrum analysis with the circular autocorrelation function is introduced to eliminate irregular noise in single-color video plethysmography. Applying the proposed method on videos collected from 39 individuals improved the estimation accuracy of instantaneous heart rate by approximately 44% over a conventional method using a linear filter. Furthermore, the proposed method also enabled more precise estimations of the heart rate than that achieved using multi-color video plethysmography.

Local Pulse Wave Velocity: Theory, Methods, Advancements, and Clinical Applications

Local pulse wave velocity (PWV) is evolving as one of the important determinants of arterial hemodynamics, localized vessel stiffening associated with several pathologies, and a host of other cardiovascular events. Although PWV was introduced over a century ago, only in recent decades, due to various technological advancements, has emphasis been directed toward its measurement from a single arterial section or from piecewise segments of a target arterial section. This emerging worldwide trend in the exploration of instrumental solutions for local PWV measurement has produced several invasive and noninvasive methods. As of yet, however, a univocal opinion on the ideal measurement method has not emerged. Neither have there been extensive comparative studies on the accuracy of the available methods. Recognizing this reality, makes apparent the need to establish guideline-recommended standards for the measurement methods and reference values, without which clinical application cannot be pursued. This paper enumerates all major local PWV measurement methods while pinpointing their salient methodological considerations and emphasizing the necessity of global standardization. Further, a summary of the advancements in measuring modalities and clinical applications is provided. Additionally, a detailed discussion on the minimally explored concept of incremental local PWV is presented along with suggestions of future research questions.

A Chair-Based Unconstrained/Nonintrusive Cuffless Blood Pressure Monitoring System Using a Two-Channel Ballistocardiogram

Hypertension is a well-known chronic disease that causes complications such as cardiovascular diseases or stroke, and thus needs to be continuously managed by using a simple system for measuring blood pressure. The existing method for measuring blood pressure uses a wrapping cuff, which makes measuring difficult for patients. To address this problem, cuffless blood pressure measurement methods that detect the peak pressure via signals measured using photoplethysmogram (PPG) and electrocardiogram (ECG) sensors and use it to calculate the pulse transit time (PTT) or pulse wave velocity (PWV) have been studied. However, a drawback of these methods is that a user must be able to recognize and establish contact with the sensor. Furthermore, the peak of the PPG or ECG cannot be detected if the signal quality drops, leading to a decrease in accuracy. In this study, a chair-type system that can monitor blood pressure using polyvinylidene fluoride (PVDF) films in a nonintrusive manner to users was developed. The proposed method also uses instantaneous phase difference (IPD) instead of PTT as the feature value for estimating blood pressure. Experiments were conducted using a blood pressure estimation model created via an artificial neural network (ANN), which showed that IPD could estimate more accurate readings of blood pressure compared to PTT, thus demonstrating the possibility of a nonintrusive blood pressure monitoring system.

Sensitivity of Video-Based Pulse Arrival Time to Dynamic Blood Pressure Changes

Estimating blood pressure (BP) from pulse arrival time (PAT) by image-based (skin video) photoplethysmography (iPPG) is of increasing interest due to the non-contact method advantage (over cuff-based methods) and potential for BP measurement to be built into portable devices such as mobile phones. The relationship between pulse transit time extracted from iPPG has been investigated during stable BP. The sensitivity of beat-to-beat iPPG-PAT to dynamic changes in BP has not been explored. This study investigated the correlation between iPPG-PAT and diastolic BP (DBP) during 1-minute seated rest and 3-minute isometric handgrip exercise. 15 healthy participants (9 female, 34±13 years) were recruited. Video was recorded from subjects' faces at 30 frames per second using a standard web-camera with simultaneous measurement of the electrocardiogram and noninvasive finger BP. The iPPG waveform was from the averaged green channel intensity of regions of the forehead or cheek. PAT was calculated from the R-wave ofthe electrocardiogram to the foot of the iPPG or finger BP waveform respectively for direct comparison. Handgrip exercise caused a steady increase in DBP (75±9 to 87±13 mmHg, p<0.001). Beat-to-beat iPPG-PAT and DBP was negatively correlated (mena ±SE -1.33±1.70 ms/mmHg, P=0.0024) as was finger-PAT (mean ±SE -0.5S ±0.39 ms/mmHg, P<0.001). The proportion of individual significant negative regression slopes between DBP and finger-PAT and between DBP and iPPG-PAT was not significantly different. Despite high variability of the correlation between iPPG-PAT and DBP among subjects, iPPG-PAT can track dynamic changes in BP.

Blood perfusion display based on video pulse wave

In this study, an easy system for monitoring dynamic blood perfusion patterns and the pulse wave velocity (PWV) has been developed by processing video images of a human body to assess blood circulation for daily management of physical conditions or for detecting persons in poor physical condition in public places. The experiment suggested that this tool can be used to easily evaluate the PWV; however, the obtained value from the video image of the face was about 1/10 of the standard value calculated from thick vessels. This difference may be related to the difference between thick vessels and thin-branched arterioles.