Monte Carlo Analysis of Optical Interactions in Reflectance and Transmittance Finger Photoplethysmography

Monte Carlo simulation of the effect of melanin concentration on light-tissue interactions in transmittance and reflectance finger photoplethysmography

Photoplethysmography (PPG) uses light to detect volumetric changes in blood, and is integrated into many healthcare devices to monitor various physiological measurements. However, an unresolved limitation of PPG is the effect of skin pigmentation on the signal and its impact on PPG based applications such as pulse oximetry. Hence, an in-silico model of the human finger was developed using the Monte Carlo (MC) technique to simulate light interactions with different melanin concentrations in a human finger, as it is the primary determinant of skin pigmentation. The AC/DC ratio in reflectance PPG mode was evaluated at source-detector separations of 1 mm and 3 mm as the convergence rate (Q), a parameter that quantifies the accuracy of the simulation, exceeded a threshold of 0.001. At a source-detector separation of 3 mm, the AC/DC ratio of light skin was 0.472 times more than moderate skin and 6.39 than dark skin at 660 nm, and 0.114 and 0.141 respectively at 940 nm. These findings are significant for the development of PPG-based sensors given the ongoing concerns regarding the impact of skin pigmentation on healthcare devices.

Tissue mimicking materials and finger phantom design for pulse oximetry

Pulse oximetry represents a ubiquitous clinical application of optics in modern medicine. Recent studies have raised concerns regarding the potential impact of confounders, such as variable skin pigmentation and perfusion, on blood oxygen saturation measurement accuracy in pulse oximeters. Tissue-mimicking phantom testing offers a low-cost, well-controlled solution for characterizing device performance and studying potential error sources, which may thus reduce the need for costly in vivo trials. The purpose of this study was to develop realistic phantom-based test methods for pulse oximetry. Material optical and mechanical properties were reviewed, selected, and tuned for optimal biological relevance, e.g., oxygenated tissue absorption and scattering, strength, elasticity, hardness, and other parameters representing the human finger's geometry and composition, such as blood vessel size and distribution, and perfusion. Relevant anatomical and physiological properties are summarized and implemented toward the creation of a preliminary finger phantom. To create a preliminary finger phantom, we synthesized a high-compliance silicone matrix with scatterers for embedding flexible tubing and investigated the addition of these scatterers to novel 3D printing resins for optical property control without altering mechanical stability, streamlining the production of phantoms with biologically relevant characteristics. Phantom utility was demonstrated by applying dynamic, pressure waveforms to produce tube volume change and resultant photoplethysmography (PPG) signals. 3D printed phantoms achieved more biologically relevant conditions compared to molded phantoms. These preliminary results indicate that the phantoms show strong potential to be developed into tools for evaluating pulse oximetry performance. Gaps, recommendations, and strategies are presented for continued phantom development.

Improving heart rate monitoring in the obese with time-of-flight photoplethysmography (TOF-PPG): a quantitative analysis of source-detector-distance effect

Commercial photoplethysmography (PPG) sensors rely on the measurement of continuous-wave diffuse reflection signals (CW-DRS) to monitor heart rate. Using Monte Carlo modeling of light propagation in skin, we quantitatively evaluate the dependence of continuous-wave photoplethysmography (CW-PPG) in commercial wearables on source-detector distance (SDD). Specifically, when SDD increases from 0.5 mm to 3.3 mm, CW-PPG signal increases by roughly 846% for non-obese (NOB) skin and roughly 683% for morbidly obese (MOB) skin. Ultimately, we introduce the concept of time-of-flight PPG (TOF-PPG) which can significantly improve heart rate signals. Our model shows that the optimized TOF-PPG improves heart rate monitoring experiences by roughly 47.9% in NOB and 93.2% in MOB when SDD = 3.3 mm is at green light. Moving forward, these results will provide a valuable source for hypothesis generation in the scientific community to improve heart rate monitoring.

Diffuse transmittance visible spectroscopy using smartphone flashlight for photoplethysmography and vital signs measurements

Photoplethysmography (PPG), with its wide range of applications, has become one of the most promising modalities for healthcare monitoring technology. In this work, we present a new PPG measurement technique based on diffuse transmittance spectroscopy (DTS) with the help of a smartphone built-in flashlight as an alternative broadband light source. The blood Volume Pulse (BVP) signal was extracted from recorded transmittance spectra at 620 nm. The results were compared with the ground truth and conventional contact finger PPG sensors. A very high correlation was found between the diffuse transmittance signal and the reference PPG signals (r = 0.997, p < 0.0001). The accuracy and root mean square error (RMSE) were 99.23% and 0.8 bpm, respectively. In addition, a Bland-Altman analysis showed a good agreement between both techniques, with a very small bias between mean paired differences of heart rate observations. A simple forward model for diffuse transmittance spectra for different levels of blood oxygen saturation is developed and supported by experimental measurements. It was also found that blood oxygen saturation (SpO2) can be estimated with the aid of DTS based smartphone flash by tracking the wavelength corresponding to the oxygenation level in the visible range between orange and red regions of the visible spectrum particularly in the range between 610 and 635 nm for 26 healthy subjects. 624 nm on average seems to be the wavelength that corresponds with the normal blood oxygenation level. These findings show the potential of DTS PPG to reliably extract cardiac frequency and estimate SpO2 with adequate accuracy. The results also demonstrate the capability of smartphone flash as a miniature visible light source for recording multispectral PPG signals and quantifying vital signs in the transmission mode at the fingertip with acceptable signal quality over a wide range of wavelengths from 550 nm to 650 nm.

Scaling of Algorithmic Bias in Pulse Oximetry with Signal-to-Noise Ratio

Recent work has noted a skin-color bias in existing pulse oximetry systems in their estimation of arterial oxygen saturation. Frequently, the algorithm used by these systems estimate a "ratio-of-ratios", called the "R-value", on their way to estimating the oxygen saturation. In this work, we focus on an "SNR-related" bias that is due to noise in measurements. We derive expressions for the SNR-related bias in R-value estimation, and observe how it scales with the signal-to-noise ratio (SNR). We show that the bias can arise at two steps of R-value estimation: in estimating the max and min of a pulsatile signal, and, additionally in taking ratios to estimate the R-value. We assess the bias resulting from the combination of the two steps, but also separate out contributions of each step. By doing so, we deduce that the bias induced in max and min estimation is likely to dominate. Because the SNR tends to get worse with higher melanin concentration, our result provides a sense of scaling of this bias with melanin concentration.

Photoplethysmography upon cold stress-impact of measurement site and acquisition mode

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.

Monte Carlo Simulation of Diffuse Optical Spectroscopy for 3D Modeling of Dental Tissues

Three-dimensional precise models of teeth are critical for a variety of dental procedures, including orthodontics, prosthodontics, and implantology. While X-ray-based imaging devices are commonly used to obtain anatomical information about teeth, optical devices offer a promising alternative for acquiring 3D data of teeth without exposing patients to harmful radiation. Previous research has not examined the optical interactions with all dental tissue compartments nor provided a thorough analysis of detected signals at various boundary conditions for both transmittance and reflectance modes. To address this gap, a GPU-based Monte Carlo (MC) method has been utilized to assess the feasibility of diffuse optical spectroscopy (DOS) systems operating at 633 nm and 1310 nm wavelengths for simulating light-tissue interactions in a 3D tooth model. The results show that the system's sensitivity to detect pulp signals at both 633 nm and 1310 nm wavelengths is higher in the transmittance compared with that in the reflectance mode. Analyzing the recorded absorbance, reflectance, and transmittance data verified that surface reflection at boundaries can improve the detected signal, especially from the pulp region in both reflectance and transmittance DOS systems. These findings could ultimately lead to more accurate and effective dental diagnosis and treatment.

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Photoplethysmography (PPG) is a widely emerging method to assess vascular health in humans. The origins of the signal of reflective PPG on peripheral arteries have not been thoroughly investigated. We aimed to identify and quantify the optical and biomechanical processes that influence the reflective PPG signal. We developed a theoretical model to describe the dependence of reflected light on the pressure, flow rate, and the hemorheological properties of erythrocytes. To verify the theory, we designed a silicone model of a human radial artery, inserted it in a mock circulatory circuit filled with porcine blood, and imposed static and pulsatile flow conditions. We found a positive, linear relationship between the pressure and the PPG and a negative, non-linear relationship, of comparable magnitude, between the flow and the PPG. Additionally, we quantified the effects of the erythrocyte disorientation and aggregation. The theoretical model based on pressure and flow rate yielded more accurate predictions, compared to the model using pressure alone. Our results indicate that the PPG waveform is not a suitable surrogate for intraluminal pressure and that flow rate significantly affects PPG. Further validation of the proposed methodology in vivo could enable the non-invasive estimation of arterial pressure from PPG and increase the accuracy of health-monitoring devices.

A Review of Skin-Wearable Sensors for Non-Invasive Health Monitoring Applications

The early detection of fatal diseases is crucial for medical diagnostics and treatment, both of which benefit the individual and society. Portable devices, such as thermometers and blood pressure monitors, and large instruments, such as computed tomography (CT) and X-ray scanners, have already been implemented to collect health-related information. However, collecting health information using conventional medical equipment at home or in a hospital can be inefficient and can potentially affect the timeliness of treatment. Therefore, on-time vital signal collection via healthcare monitoring has received increasing attention. As the largest organ of the human body, skin delivers significant signals reflecting our health condition; thus, receiving vital signals directly from the skin offers the opportunity for accessible and versatile non-invasive monitoring. In particular, emerging flexible and stretchable electronics demonstrate the capability of skin-like devices for on-time and continuous long-term health monitoring. Compared to traditional electronic devices, this type of device has better mechanical properties, such as skin conformal attachment, and maintains compatible detectability. This review divides the health information that can be obtained from skin using the sensor aspect's input energy forms into five categories: thermoelectrical signals, neural electrical signals, photoelectrical signals, electrochemical signals, and mechanical pressure signals. We then summarize current skin-wearable health monitoring devices and provide outlooks on future development.

Fiber-based quantum-dot pulse oximetry for wearable health monitoring with high wavelength selectivity and photoplethysmogram sensitivity

Increasing demand for real-time healthcare monitoring is leading to advances in thin and flexible optoelectronic device-based wearable pulse oximetry. Most previous studies have used OLEDs for this purpose, but did not consider the side effects of broad full-width half-maximum (FWHM) characteristics and single substrates. In this study, we performed SpO₂ measurement using a fiber-based quantum-dot pulse oximetry (FQPO) system capable of mass production with a transferable encapsulation technique, and a narrow FWHM of about 30 nm. Based on analyses we determined that uniform angular narrow FWHM-based light sources are important for accurate SpO₂ measurements through multi-layer structures and human skin tissues. The FQPO was shown to have improved photoplethysmogram (PPG) signal sensitivity with no waveguide-mode noise signal, as is typically generated when using a single substrate (30-50%). We successfully demonstrate improved SpO₂ measurement accuracy as well as all-in-one clothing-type pulse oximetry with FQPO.

The past, present, and future of sleep quality assessment and monitoring

Sleep quality is considered to be an individual's self-satisfaction with all aspects of the sleep experience. Good sleep not only improves a person's physical, mental and daily functional health, but also improves the quality-of-life level to some extent. In contrast, chronic sleep deprivation can increase the risk of diseases such as cardiovascular diseases, metabolic dysfunction and cognitive and emotional dysfunction, and can even lead to increased mortality. The scientific evaluation and monitoring of sleep quality is an important prerequisite for safeguarding and promoting the physiological health of the body. Therefore, we have compiled and reviewed the existing methods and emerging technologies commonly used for subjective and objective evaluation and monitoring of sleep quality, and found that subjective sleep evaluation is suitable for clinical screening and large-scale studies, while objective evaluation results are more intuitive and scientific, and in the comprehensive evaluation of sleep, if we want to get more scientific monitoring results, we should combine subjective and objective monitoring and dynamic monitoring.

Non-Invasive In Vivo Estimation of HbA1c Using Monte Carlo Photon Propagation Simulation: Application of Tissue-Segmented 3D MRI Stacks of the Fingertip and Wrist for Wearable Systems

The early diagnosis of diabetes mellitus in normal people or maintaining stable blood sugar concentrations in diabetic patients requires frequent monitoring of the blood sugar levels. However, regular monitoring of the sugar levels is problematic owing to the pain and inconvenience associated with pricking the fingertip or using minimally invasive patches. In this study, we devise a noninvasive method to estimate the percentage of the in vivo glycated hemoglobin (HbA1c) values from Monte Carlo photon propagation simulations, based on models of the wrist using 3D magnetic resonance (MR) image data. The MR image slices are first segmented for several different tissue types, and the proposed Monte Carlo photon propagation system with complex composite tissue support is then used to derive several models for the fingertip and wrist sections with different wavelengths of light sources and photodetector arrangements. The Pearson r values for the estimated percent HbA1c values are 0.94 and 0.96 for the fingertip transmission- and reflection-type measurements, respectively. This is found to be the best among the related studies. Furthermore, a single-detector multiple-source arrangement resulted in a Pearson r value of 0.97 for the wrist. The Bland-Altman bias values were found to be -0.003 ± 0.36, 0.01 ± 0.25, and 0.01 ± 0.21, for the two fingertip and wrist models, respectively, which conform to the standards of the current state-of-the-art invasive point-of-care devices. The implementation of these algorithms will be a suitable alternative to the invasive state-of-the-art methods.

A Computational Modeling and Simulation Workflow to Investigate the Impact of Patient-Specific and Device Factors on Hemodynamic Measurements from Non-Invasive Photoplethysmography

Cardiovascular disease is the leading cause of death globally. To provide continuous monitoring of blood pressure (BP), a parameter which has shown to improve health outcomes when monitored closely, many groups are trying to measure blood pressure via noninvasive photoplethysmography (PPG). However, the PPG waveform is subject to variation as a function of patient-specific and device factors and thus a platform to enable the evaluation of these factors on the PPG waveform and subsequent hemodynamic parameter prediction would enable device development. Here, we present a computational workflow that combines Monte Carlo modeling (MC), gaussian combination, and additive noise to create synthetic dataset of volar fingertip PPG waveforms representative of a diverse cohort. First, MC is used to determine PPG amplitude across age, skin tone, and device wavelength. Then, gaussian combination generates accurate PPG waveforms, and signal processing enables data filtration and feature extraction. We improve the limitations of current synthetic PPG frameworks by enabling inclusion of physiological and anatomical effects from body site, skin tone, and age. We then show how the datasets can be used to examine effects of device characteristics such as wavelength, analog to digital converter specifications, filtering method, and feature extraction. Lastly, we demonstrate the use of this framework to show the insensitivity of a support vector machine predictive algorithm compared to a neural network and bagged trees algorithm.

Mechanical Testing of Artificial Vessels and Tissues for Photoplethysmography Phantoms

Various studies have looked at the efficiency of artificial vessel and tissue networks in the study of photoplethysmography (PPG) in an effort to better understand the origin of various morphological features present in the signal. Whilst there are all reasonable attempts made to replicate geometrical features such as vessel depth, vessel wall thickness and diameter etc., not many studies have attempted to replicate the mechanical properties such as vessel elasticity and tissue compressibility. This study reports two methods for tissue mechanical testing for the analysis of vessel elasticity and tissue compressibility. A two-part polydimethylsiloxane (PDMS) was used as a base material for both tissue and vessel construction, and the properties altered by changing the curing component ratio. Tissue compression properties were investigated using an industrially calibrated materials testing device using the protocol from the ASTM 0575-91 testing method. Vessel elasticity was investigated using a custom method and apparatus to report vessel diameter and length change simultaneously. Tissue compressive properties proved reasonably easy to replicate through catalyst alteration, however the vessel elasticity properties were found to be higher than expected at all reasonable catalyst ratios. The property of hyper-elasticity was observed in the artificial vessels though, leading to the conclusion that alternative material recipes or construction methods may be needed to correctly replicate the expected mechanical characteristics. Clinical Relevance- The latest generation of health monitoring devices, especially those that are wearable and used widely by individuals wishing to monitor their health daily are becoming smarter and more sophisticated in their functionality. The majority of such devices use photoplethysmography (PPG) as their primary monitoring technique. Being able to replicate the PPG in a phantom allows the continued study and development of devices, and to improve their functionality without the continued need for extensive user-testing.

Monte Carlo Simulation of the Effect of Human Skin Melanin in Light-Tissue Interactions

Recent reports have highlighted the potential challenges skin pigmentation can have in the accurate estimation of arterial oxygen saturation when using a pulse oximeter. Pulse oximeters work on the principle of photoplethysmography (PPG), an optical technique used for the assessment of volumetric changes in vascular tissue. The primary aim of this research is to investigate the effect of melanin on tissue when utilising the technique of PPG. To address this, a Monte Carlo (MC) light-tissue interaction model is presented to explore the behaviour of melanin in the visible range in the epidermis. A key novelty in this paper is the ability to model the Modified Beer Lambert Law (MBLL) through a fully functional three-dimensional (3D) model in reflective optical geometry. Maximum photon penetration depth was achieved by red light, however limited bio-optical information was retrieved by moderately and darkly pigmented skin at source-detector separations of less than 3 mm. The current MC model can be modified to provide a more realistic representation of absorption and scattering processes in skin.

Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals

Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure the blood pressure, which may be uncomfortable and sometimes burdensome to the subjects. Therefore, in this study, we propose a cuffless blood pressure estimation model based on Monte Carlo simulation (MCS). We propose a heterogeneous finger model for the MCS at wavelengths of 905 nm and 940 nm. After recording the photon intensities from the MCS over a certain range of blood pressure values, the actual photoplethysmography (PPG) signals were used to estimate blood pressure. We used both publicly available and self-made datasets to evaluate the performance of the proposed model. In case of the publicly available dataset for transmission-type MCS, the mean absolute errors are 3.32 ± 6.03 mmHg for systolic blood pressure (SBP), 2.02 ± 2.64 mmHg for diastolic blood pressure (DBP), and 1.76 ± 2.8 mmHg for mean arterial pressure (MAP). The self-made dataset is used for both transmission- and reflection-type MCSs; its mean absolute errors are 2.54 ± 4.24 mmHg for SBP, 1.49 ± 2.82 mmHg for DBP, and 1.51 ± 2.41 mmHg for MAP in the transmission-type case as well as 3.35 ± 5.06 mmHg for SBP, 2.07 ± 2.83 mmHg for DBP, and 2.12 ± 2.83 mmHg for MAP in the reflection-type case. The estimated results of the SBP and DBP satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standards and are within Grade A according to the British Hypertension Society (BHS) standards. These results show that the proposed model is efficient for estimating blood pressures using fingertip PPG signals.

Noninvasive Estimation of Glycated Hemoglobin In-Vivo Based on Photon Diffusion Theory and Genetic Symbolic Regression Models

The diagnosis and management of diabetes require frequent monitoring of blood sugar levels. Prolonged exposure of most of the monosaccharides in the bloodstream results in the glycation of hemoglobin. This glycated hemoglobin (HbA1c) based test plays an important role to avoid diabetic complications. However, noninvasive estimation of HbA1c is a very new, promising, and challenging topic in modern bioengineering scopes. The purpose of this study is to develop and verify mathematical models in order to quantify the glycated hemoglobin in-vivo percentage non-invasively. This research utilized photon diffusion theory to develop the finger models and genetic symbolic regression methods to solve the models to estimate the level of glycated hemoglobin in the blood. The validation of these models with human participants indicated a high degree of correlation (0.887 and 0.907 Pearsons r value), and high precision (2.56% and 2.96% coefficient of variation (%CV)) for transmission and reflection type noninvasive digital volume pulse-based signals. This research will be a breakthrough for the application of noninvasive HbA1c estimation.

Thoracic Outlet Syndrome: Fingertip Cannot Replace Forearm Photoplethysmography in the Evaluation of Positional Venous Outflow Impairments

Objective: Fingertip photoplethysmography (PPG) resulting from high-pass filtered raw PPG signal is often used to record arterial pulse changes in patients with suspected thoracic outlet syndrome (TOS). Results from venous (low-pass filtered raw signal) forearm PPG (V-PPG) during the Candlestick-Prayer (Ca + Pra) maneuver were recently classified into four different patterns in patients with suspected TOS, two of which are suggestive of the presence of outflow impairment. We aimed to test the effect of probe position (fingertip vs. forearm) and of red (R) vs. infrared (IR) light wavelength on V-PPG classification and compared pattern classifications with the results of ultrasound (US).

Methods: In patients with suspected TOS, we routinely performed US imaging (US + being the presence of a positional compression) and Ca + Pra tests with forearm V-PPG_IR. We recruited patients for a Ca + Pra maneuver with the simultaneous fingertip and forearm V-PPG_R. The correlation of each V-PPG recording to each of the published pattern profiles was calculated. Each record was classified according to the patterns for which the coefficient of correlation was the highest. Cohen’s kappa test was used to determine the reliability of classification among forearm V-PPG_IR, fingertip V-PPG_R, and forearm V-PPG_R.

Results: We obtained 40 measurements from 20 patients (40.2 ± 11.3 years old, 11 males). We found 13 limbs with US + results, while V-PPG suggested the presence of venous outflow impairment in 27 and 20 limbs with forearm V-PPG_IR and forearm V-PPG_R, respectively. Fingertip V-PPG_R provided no patterns suggesting outflow impairment.

Conclusion: We found more V-PPG patterns suggesting venous outflow impairment than US + results. Probe position is essential if aiming to perform upper-limb V-PPG during the Ca + Pra maneuver in patients with suspected TOS. V-PPG during the Ca + Pra maneuver is of low cost and easy and provides reliable, recordable, and objective evidence of forearm swelling. It should be performed on the forearm (close to the elbow) with either PPG_R or PPG_IR but not at the fingertip level.

Monte Carlo analysis of optical heart rate sensors in commercial wearables: the effect of skin tone and obesity on the photoplethysmography (PPG) signal

Commercially available wearable devices have been used for fitness and health management and their demand has increased over the last ten years. These "general wellness" and heart-rate monitoring devices have been cleared by the Food and Drug Administration for over-the-counter use, yet anecdotal and more systematic reports seem to indicate that their error is higher when used by individuals with elevated skin tone and high body mass index (BMI). In this work, we used Monte Carlo modeling of a photoplethysmography (PPG) signal to study the theoretical limits of three different wearable devices (Apple Watch series 5, Fitbit Versa 2 and Polar M600) when used by individuals with a BMI range of 20 to 45 and a Fitzpatrick skin scale 1 to 6. Our work shows that increased BMI and skin tone can induce a relative loss of signal of up to 61.2% in Fitbit versa 2, 32% in Apple S5 and 32.9% in Polar M600 when considering the closest source-detector pair configuration in these devices.

Brain Light-Tissue Interaction Modelling: Towards a non-invasive sensor for Traumatic Brain Injury

Traumatic brain injury (TBI) is one of the leading causes of death worldwide, yet there is no systematic approach to monitor TBI non-invasively. The main motivation of this work is to create new knowledge relating to light brain interaction using a Monte Carlo Model, which could aid in the development of non-invasive optical sensors for the continuous assessment of TBI. To this aim, a multilayer model tissue-model of adult human head was developed and explored at the near-infrared optical wavelength. Investigation reveals that maximum light (40-50%) is absorbed in the skull and the minimum light is absorbed in the subarachnoid space (0-1%). It was found that the absorbance of light decreases with increasing source-detector separation up to 3cm where light travels through the subarachnoid space, after which the absorbance increases with the increasing separation. Such information will be helpful towards the modelling of neurocritical brain tissue followed by the sensor development.

Monte Carlo Characterization of Short-Wave Infrared Optical Wavelengths for Biosensing Applications

Short-wave infrared (SWIR) spectroscopy has shown great promise in probing the composition of biological tissues. Currently there exists an enormous drive amongst researchers to design and develop SWIR-based optical sensors that can predict the concentration of various biomarkers non-invasively. However, there is limited knowledge regarding the interaction of SWIR light with vascular tissue, especially in terms of parameters like the optimal source-detector separation, light penetration depth, optical pathlength, etc., all of which are essential components in designing optical sensors. With the aim to determine these parameters, Monte Carlo simulations were carried out to examine the interaction of SWIR light with vascular skin. SWIR photons were found to penetrated only 1.3 mm into the hypodermal fat layer. The highest optical pathlength and penetration depths were seen at 1mm source-detector separation, and the lowest being 0.7mm. Although the optical pathlength varied significantly with increasing source-detector separation at SWIR wavelengths, penetration depth remained constant. This may explain why collecting optical spectra from depth of tissue at SWIR wavelengths is more challenging than collecting optical spectra from near-infrared wavelengths, where both the optical pathlength and penetration depth change rapidly with source-detector separation.

Noninvasive In Vivo Estimation of Blood-Glucose Concentration by Monte Carlo Simulation

Continuous monitoring of blood-glucose concentrations is essential for both diabetic and nondiabetic patients to plan a healthy lifestyle. Noninvasive in vivo blood-glucose measurements help reduce the pain of piercing human fingertips to collect blood. To facilitate noninvasive measurements, this work proposes a Monte Carlo photon simulation-based model to estimate blood-glucose concentration via photoplethysmography (PPG) on the fingertip. A heterogeneous finger model was exposed to light at 660 nm and 940 nm in the reflectance mode of PPG via Monte Carlo photon propagation. The bio-optical properties of the finger model were also deduced to design the photon simulation model for the finger layers. The intensities of the detected photons after simulation with the model were used to estimate the blood-glucose concentrations using a supervised machine-learning model, XGBoost. The XGBoost model was trained with synthetic data obtained from the Monte Carlo simulations and tested with both synthetic and real data (n = 35). For testing with synthetic data, the Pearson correlation coefficient (Pearson’s r) of the model was found to be 0.91, and the coefficient of determination (R²) was found to be 0.83. On the other hand, for tests with real data, the Pearson’s r of the model was 0.85, and R² was 0.68. Error grid analysis and Bland–Altman analysis were also performed to confirm the accuracy. The results presented herein provide the necessary steps for noninvasive in vivo blood-glucose concentration estimation.

Sources of Inaccuracy in Photoplethysmography for Continuous Cardiovascular Monitoring

Photoplethysmography (PPG) is a low-cost, noninvasive optical technique that uses change in light transmission with changes in blood volume within tissue to provide information for cardiovascular health and fitness. As remote health and wearable medical devices become more prevalent, PPG devices are being developed as part of wearable systems to monitor parameters such as heart rate (HR) that do not require complex analysis of the PPG waveform. However, complex analyses of the PPG waveform yield valuable clinical information, such as: blood pressure, respiratory information, sympathetic nervous system activity, and heart rate variability. Systems aiming to derive such complex parameters do not always account for realistic sources of noise, as testing is performed within controlled parameter spaces. A wearable monitoring tool to be used beyond fitness and heart rate must account for noise sources originating from individual patient variations (e.g., skin tone, obesity, age, and gender), physiology (e.g., respiration, venous pulsation, body site of measurement, and body temperature), and external perturbations of the device itself (e.g., motion artifact, ambient light, and applied pressure to the skin). Here, we present a comprehensive review of the literature that aims to summarize these noise sources for future PPG device development for use in health monitoring.

Synthetic photoplethysmography (PPG) of the radial artery through parallelized Monte Carlo and its correlation to body mass index (BMI)

Cardiovascular disease is one of the leading causes of death in the United States and obesity significantly increases the risk of cardiovascular disease. The measurement of blood pressure (BP) is critical in monitoring and managing cardiovascular disease hence new wearable devices are being developed to make BP more accessible to physicians and patients. Several wearables utilize photoplethysmography from the wrist vasculature to derive BP assessment although many of these devices are still at the experimental stage. With the ultimate goal of supporting instrument development, we have developed a model of the photoplethysmographic waveform derived from the radial artery at the volar surface of the wrist. To do so we have utilized the relation between vessel biomechanics through Finite Element Method and Monte Carlo light transport model. The model shows similar features to that seen in PPG waveform captured using an off the shelf device. We observe the influence of body mass index on the PPG signal. A degradation the PPG signal of up to 40% in AC to DC signal ratio was thus observed.

Development of a Portable All-Wavelength PPG Sensing Device for Robust Adaptive-Depth Measurement: A Spectrometer Approach with a Hydrostatic Measurement Example

Photoplethysmography (PPG), a noninvasive optical sensing technology, has been widely used to measure various physiological indices. Over-the-counter PPG devices are typically composed of a single-wavelength light source, namely, single-wavelength PPG (SW-PPG). It is known that signals of SW-PPG are easily contaminated or distorted by measurement conditions such as motion artifacts, wearing pressure, and skin type. Since lights of different wavelengths can penetrate skin tissues at different depths, how to effectively construct a multiwavelength PPG (MW-PPG) device or even an all-wavelength PPG (AW-PPG) device has attracted great attention. There is also a very interesting question, that is, what could be the potential benefits of using MW-PPG or AW-PPG devices? This paper demonstrates the construction of an AW-PPG portable device and conducts a preliminary evaluation. The presented device consists of four light-emitting diodes, a chip-scale spectrometer, a microcontroller, a Bluetooth Low Energy transceiver, and a phone app. The maximum ratio combining algorithm (MRC) is used to combine the PPG signals derived from different wavelengths to achieve a better signal-to-noise ratio (S/N). The PPG signals from the developed MRC-AW-PPG device versus those from the conventional SW-PPG device are compared in terms of different hydrostatic pressure conditions. It has been observed that the MRC-AW-PPG device can provide more stable PPG signals than that of a conventional PPG device. The results shine a light on the potential benefits of using multiple wavelengths for the next generation of noninvasive PPG sensing.

Investigating the origin of photoplethysmography using a multiwavelength Monte Carlo model

Photoplethysmography (PPG) is a photometric technique used for the measurement of volumetric changes in the blood. The recent interest in new applications of PPG has invigorated more fundamental research regarding the origin of the PPG waveform, which since its discovery in 1937, remains inconclusive. A handful of studies in the recent past have explored various hypotheses for the origin of PPG. These studies relate PPG to mechanical movement, red blood cell orientation or blood volume variations.

OBJECTIVE

Recognising the significance and need to corroborate a theory behind PPG formation, the present work rigorously investigates the origin of PPG based on a realistic model of light-tissue interactions.

APPROACH

A three-dimensional comprehensive Monte Carlo model of finger-PPG was developed and explored to quantify the optical entities pertinent to PPG (e.g. absorbance, reflectance, and penetration depth) as the functions of multiple wavelengths and source-detector separations. Complementary to the simulations, a pilot in vivo investigation was conducted on eight healthy volunteers. PPG signals were recorded using a custom-made multiwavelength sensor with an adjustable source-detector separation.

MAIN RESULTS

Simulated results illustrate the distribution of photon-tissue interactions in the reflectance PPG geometry. The depth-selective analysis quantifies the contributions of the dermal and subdermal tissue layers in the PPG wave formation. A strong negative correlation (r = -0.96) is found between the ratios of the simulated absorbances and measured PPG amplitudes.

SIGNIFICANCE

This work quantified for the first time the contributions of different tissue layers and sublayers in the formation of the PPG signal.

Novel Polydimethylsiloxane (PDMS) Pulsatile Vascular Tissue Phantoms for the In-Vitro Investigation of Light Tissue Interaction in Photoplethysmography

Currently there exists little knowledge or work in phantoms for the in-vitro evaluation of photoplethysmography (PPG), and its' relationship with vascular mechanics. Such phantoms are needed to provide robust, basic scientific knowledge, which will underpin the current efforts in developing new PPG technologies for measuring or estimating blood pressure, blood flow and arterial stiffness, to name but a few. This work describes the design, fabrication and evaluation of finger tissue-simulating pulsatile phantoms with integrated custom vessels. A novel technique has been developed to produce custom polydimethylsiloxane (PDMS) vessels by a continuous dip-coating process. This process can accommodate the production of different sized vessel diameters (1400-2500 µm) and wall thicknesses (56-80 µm). These vessels were embedded into a mould with a solution of PDMS and India ink surrounding them. A pulsatile pump experimental rig was set up to test the phantoms, where flow rate (1-12 L·min-1), heart rate (40-120 bpm), and total resistance (0-100% resistance clamps) could be controlled on demand. The resulting flow profiles approximates human blood flow, and the detected contact PPG signal (red and infrared) from the phantom closely resembles the morphology of in-vivo PPG waveforms with signal-to-noise ratios of 38.16 and 40.59 dB, for the red and infrared wavelengths, respectively. The progress made by this phantom development will help in obtaining new knowledge in the behaviour of PPG's under differing flow conditions, optical tissue properties and differing vessel stiffness.

A Wristwatch-Based Wireless Sensor Platform for IoT Health Monitoring Applications

A wristwatch-based wireless sensor platform for IoT wearable health monitoring applications is presented. The paper describes the platform in detail, with a particular focus given to the design of a novel and compact wireless sub-system for 868 MHz wristwatch applications. An example application using the developed platform is discussed for arterial oxygen saturation (SpO₂) and heart rate measurement using optical photoplethysmography (PPG). A comparison of the wireless performance in the 868 MHz and the 2.45 GHz bands is performed. Another contribution of this work is the development of a highly integrated 868 MHz antenna. The antenna structure is printed on the surface of a wristwatch enclosure using laser direct structuring (LDS) technology. At 868 MHz, a low specific absorption rate (SAR) of less than 0.1% of the maximum permissible limit in the simulation is demonstrated. The measured on-body prototype antenna exhibits a −10 dB impedance bandwidth of 36 MHz, a peak realized gain of −4.86 dBi and a radiation efficiency of 14.53% at 868 MHz. To evaluate the performance of the developed 868 MHz sensor platform, the wireless communication range measurements are performed in an indoor environment and compared with a commercial Bluetooth wristwatch device.

In silico and in vivo investigations using an endocavitary photoplethysmography sensor for tissue viability monitoring

SIGNIFICANCE

Colorectal cancer is one of the major causes of cancer-related deaths worldwide. Surgical removal of the cancerous growth is the primary treatment for this disease. A colorectal cancer surgery, however, is often unsuccessful due to the anastomotic failure that may occur following the surgical incision. Prevention of an anastomotic failure requires continuous monitoring of intestinal tissue viability during and after colorectal surgery. To date, no clinical technology exists for the dynamic and continuous monitoring of the intestinal perfusion.

AIM

A dual-wavelength indwelling bowel photoplethysmography (PPG) sensor for the continuous monitoring of intestinal viability was proposed and characterized through a set of in silico and in vivo investigations.

APPROACH

The in silico investigation was based on a Monte Carlo model that was executed to quantify the variables such as penetration depth and detected intensity with respect to the sensor-tissue separations and tissue perfusion. Utilizing the simulated information, an indwelling reflectance PPG sensor was designed and tested on 20 healthy volunteers. Two sets of in vivo studies were performed using the driving current intensities 20 and 40 mA for a comparative analysis, using buccal tissue as a proxy tissue-site.

RESULTS

Both simulated and experimental results showed the efficacy of the sensor to acquire good signals through the "contact" to a "noncontact" separation of 5 mm. A very slow wavelength-dependent variation was shown in the detected intensity at the normal and hypoxic states of the tissue, whereas a decay in the intensity was found with the increasing submucosal-blood volume. The simulated detected-to-incident-photon-ratio and the experimental signal-to-noise ratio exhibited strong positive correlations, with the Pearson product-moment correlation coefficient R ranging between 0.65 and 0.87.

CONCLUSIONS

The detailed feasibility analysis presented will lead to clinical trials utilizing the proposed sensor.

Design of Multi-Wavelength Optical Sensor Module for Depth-Dependent Photoplethysmography

The multi-wavelength photoplethysmography sensors were introduced to measure depth-dependent blood volume based on that concept that the longer the light wavelength, the deeper the penetration depth near visible spectrum band. In this study, we propose an omnidirectional optical sensor module that can measure photoplethysmogram while using multiple wavelengths, and describe implementation detail. The developed sensor is manufactured by making a hole in a metal plate and mounting an LED therein, and it has four wavelength LEDs of blue (460 nm), green (530 nm), red (660 nm), and IR (940 nm), being arranged concentrically around a photodetector. Irradiation light intensity was measured by photoluminescent test, and photoplethymogram was measured with each wavelength simultaneously at a periphery of the human body such as fingertip, earlobe, toe, forehead, and wrist, in order to evaluate the developed sensor. As a result, the developed sensor module showed a linear increase of irradiating light intensity according to the number of LEDs increases, and pulsatile waveforms were observed at all four wavelengths in all measuring sites.

A Novel Photoplethysmography Sensor for Vital Signs Monitoring from the Human Trachea

Current pulse oximeter sensors can be challenged in working accurately and continuously in situations of reduced periphery perfusion, especially among anaesthetised patients. A novel tracheal photoplethysmography (PPG) sensor has been developed in an effort to address the limitations of current pulse oximeters. The sensor has been designed to estimate oxygen saturation (SpO2) and pulse rate, and has been manufactured on a flexible printed circuit board (PCB) that can adhere to a standard endotracheal (ET) tube. A pilot clinical trial was carried out as a feasibility study on 10 anaesthetised patients. Good quality PPGs from the trachea were acquired at red and infrared wavelengths in all patients. The mean SpO2 reading for the ET tube was 97.1% (SD 1.0%) vs. the clinical monitor at 98.7% (SD 0.7%). The mean pulse rate for the ET sensor was 65.4 bpm (SD 10.0 bpm) vs. the clinical monitor at 64.7 bpm (SD 9.9 bpm). This study supports the hypothesis that the human trachea could be a suitable monitoring site of SpO2 and other physiological parameters, at times where the periphery circulation might be compromised.

A Multilayer Monte Carlo Model for the Investigation of Optical Path and Penetration Depth at Different Perfusion States of the Colon

There is a great interest in monitoring the oxygen supply delivered to the colon. Insufficient oxygen delivery may lead to hypoxia, sepsis, multiorgan dysfunction and death. For assessing colonic perfusion, more information and understanding is required relating to the light-interaction within the colonic tissue. A multilayer Monte Carlo model of a healthy human colon has been developed to investigate the light-tissue behavior during different perfusion states within the mucosal layer of the colon. Results from a static multilayer model of optical path and reflectance at two wavelengths, 660 nm and 880 nm, through colon tissue, containing different volume fractions of blood with a fixed oxygen saturation are presented. The effect on the optical path and penetration depth with varying blood volumes within the mucosa for each wavelength has been demonstrated. The simulation indicated both wavelengths of photons penetrated similar depths, entering the muscularis layer.

Perfusion Changes at the Forehead Measured by Photoplethysmography during a Head-Down Tilt Protocol

Photoplethysmography (PPG) signals from the forehead can be used in pulse oximetry as they are less affected by vasoconstriction compared to fingers. However, the increase in venous blood caused by the positioning of the patient can deteriorate the signals and cause erroneous estimations of the arterial oxygen saturation. To date, there is no method to measure this venous presence under the PPG sensor. This study investigates the feasibility of using PPG signals from the forehead in an effort to estimate relative changes in haemoglobin concentrations that could reveal these posture-induced changes. Two identical reflectance PPG sensors were placed on two different positions on the forehead (above the eyebrow and on top of a large vein) in 16 healthy volunteers during a head-down tilt protocol. Relative changes in oxygenated (ΔHbO2), reduced (ΔHHb) and total (ΔtHb) haemoglobin were estimated from the PPG signals and the trends were compared with reference Near Infrared Spectroscopy (NIRS) measurements. Also, the signals from the two PPG sensors were analysed in order to reveal any difference due to the positioning of the sensor. ΔHbO2, ΔHHb and ΔtHb estimated from the forehead PPGs trended well with the same parameters from the reference NIRS. However, placing the sensor over a large vasculature reduces trending against NIRS, introduces biases as well as increases the variability of the changes in ΔHHb. Forehead PPG signals can be used to measure perfusion changes to reveal venous pooling induced by the positioning of the subject. Placing the sensor above the eyebrow and away from large vasculature avoids biases and large variability in the measurements.