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

Cuffless Blood Pressure in clinical practice: challenges, opportunities and current limits

Background: Cuffless blood pressure measurement technologies have attracted significant attention for their potential to transform cardiovascular monitoring.Methods: This updated narrative review thoroughly examines the challenges, opportunities, and limitations associated with the implementation of cuffless blood pressure monitoring systems.Results: Diverse technologies, including photoplethysmography, tonometry, and ECG analysis, enable cuffless blood pressure measurement and are integrated into devices like smartphones and smartwatches. Signal processing emerges as a critical aspect, dictating the accuracy and reliability of readings. Despite its potential, the integration of cuffless technologies into clinical practice faces obstacles, including the need to address concerns related to accuracy, calibration, and standardization across diverse devices and patient populations. The development of robust algorithms to mitigate artifacts and environmental disturbances is essential for extracting clear physiological signals. Based on extensive research, this review emphasizes the necessity for standardized protocols, validation studies, and regulatory frameworks to ensure the reliability and safety of cuffless blood pressure monitoring devices and their implementation in mainstream medical practice. Interdisciplinary collaborations between engineers, clinicians, and regulatory bodies are crucial to address technical, clinical, and regulatory complexities during implementation. In conclusion, while cuffless blood pressure monitoring holds immense potential to transform cardiovascular care. The resolution of existing challenges and the establishment of rigorous standards are imperative for its seamless incorporation into routine clinical practice.Conclusion: The emergence of these new technologies shifts the paradigm of cardiovascular health management, presenting a new possibility for non-invasive continuous and dynamic monitoring. The concept of cuffless blood pressure measurement is viable and more finely tuned devices are expected to enter the market, which could redefine our understanding of blood pressure and hypertension.

The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research

We propose a categorization of smartwatch use in the health care sector into 3 key functional domains: monitoring, nudging, and predicting. Monitoring involves using smartwatches within medical treatments to track health data, nudging pertains to individual use for health purposes outside a particular medical setting, and predicting involves using aggregated user data to train machine learning algorithms to predict health outcomes. Each domain offers unique contributions to health care, yet there is a lack of nuanced discussion in existing research. This paper not only provides an overview of recent technological advancements in consumer smartwatches but also explores the 3 domains in detail, culminating in a comprehensive summary that anticipates the future value and impact of smartwatches in health care. By dissecting the interconnected challenges and potentials, this paper aims to enhance the understanding and effective deployment of smartwatches in value-based health care.

Smartwatch Biometrics in the Electronic Medical Record: Time for a New Vital Sign?

Smartphone biometrics in the EMR: is the 5th vital sign here? @JCOCCI_ASCO commentary by Sankaran and @RahulBanerjeeMD here.

Exploring the bias: how skin color influences oxygen saturation readings via Monte Carlo simulations

Significance

Our goal is to understand the root cause of reported oxygen saturation (SpO 2 ) overestimation in heavily pigmented skin types to devise solutions toward enabling equity in pulse oximeter designs.

Aim

We aim to gain theoretical insights into the effect of skin tone onSpO 2 - R curves using a three-dimensional, four-layer tissue model representing a finger.

Approach

A finger tissue model, comprising the epidermis, dermis, two arteries, and a bone, was developed using a Monte Carlo-based approach in the MCmatlab software. Two skin tones-light and dark-were simulated by adjusting the absorption and scattering properties within the epidermal layer. Following this,SpO 2 - R curves were generated in various tissue configurations, including transmission and reflection modes using red and infrared wavelengths. In addition, the influence of source-detector (SD) separation distances on both light and dark skin tissue models was studied.

Results

In transmission mode,SpO 2 - R curves did not deviate with changes in skin tones because both pulsatile and non-pulsatile terms experienced equal attenuation at red and infrared wavelengths. However, in reflection mode, measurable variations inSpO 2 - R curves were evident. This was due to differential attenuation of the red components, which resulted in a lower perfusion index at the red wavelength in darker skin. As the SD separation increased, the effect of skin tone onSpO 2 - R curves in reflection mode became less pronounced, with the largest SD separation exhibiting effects similar to those observed in transmission mode.

Conclusions

Monte Carlo simulations have demonstrated that different light pathlengths within the tissue contribute to the overestimation ofSpO 2 in people with darker skin in reflection mode pulse oximetry. Increasing the SD separation may mitigate the effect of skin tone onSpO 2 readings. These trends were not observed in transmission mode; however, further planned research using more complex models of the tissue is essential.

Photoplethysmography based atrial fibrillation detection: a continually growing field

Objective. Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant health ramifications, including an elevated susceptibility to ischemic stroke, heart disease, and heightened mortality. Photoplethysmography (PPG) has emerged as a promising technology for continuous AF monitoring for its cost-effectiveness and widespread integration into wearable devices. Our team previously conducted an exhaustive review on PPG-based AF detection before June 2019. However, since then, more advanced technologies have emerged in this field.Approach. This paper offers a comprehensive review of the latest advancements in PPG-based AF detection, utilizing digital health and artificial intelligence (AI) solutions, within the timeframe spanning from July 2019 to December 2022. Through extensive exploration of scientific databases, we have identified 57 pertinent studies.Significance. Our comprehensive review encompasses an in-depth assessment of the statistical methodologies, traditional machine learning techniques, and deep learning approaches employed in these studies. In addition, we address the challenges encountered in the domain of PPG-based AF detection. Furthermore, we maintain a dedicated website to curate the latest research in this area, with regular updates on a regular basis.

State of the science and recommendations for using wearable technology in sleep and circadian research

Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.

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.

Quarter-Annulus Si-Photodetector with Equal Inner and Outer Radii of Curvature for Reflective Photoplethysmography Sensors

Reflection-type photoplethysmography (PPG) pulse sensors used in wearable smart watches, true wireless stereo, etc., have been recently considered a key component for monitoring biological signals such as heart rate, SPO3, and blood pressure. Typically, the optical front end (OFE) of these PPG sensors is heterogeneously configured and packaged with light sources and receiver chips. In this paper, a novel quarter-annulus photodetector (NQAPD) with identical inner and outer radii of curvature has been developed using a plasma dicing process to realize a ring-type OFE receiver, which maximizes manufacturing efficiency and increases the detector collection area by 36.7% compared to the rectangular PD. The fabricated NQAPD exhibits a high quantum efficiency of over 90% in the wavelength of 500 nm to 740 nm and the highest quantum efficiency of 95% with a responsivity of 0.41 A/W at the wavelength of 530 nm. Also, the NQAPD is shown to increase the SNR of the PPG signal by 5 to 7.6 dB compared to the eight rectangular PDs. Thus, reflective PPG sensors constructed with NQAPD can be applied to various wearable devices requiring low power consumption, high performance, and cost-effectiveness.

Defining the Dimensions of Diversity to Promote Inclusion in the Digital Era of Health Care: A Lexicon

The pandemic provided a stark reminder of the inequities faced by populations historically marginalized by the health care system and accelerated the adoption of digital health technologies to drive innovation. Digital health technologies' purported promises to reduce inefficiencies and costs, improve access and health outcomes, and empower patients add a new level of urgency to health equity. As conventional medicine shifts toward digital medicine, we have the opportunity to intentionally develop and deploy digital health technologies with an inclusion focus. The first step is ensuring that the multiple dimensions of diversity are captured. We propose a lexicon that encompasses elements critical for implementing an inclusive approach to advancing health care quality and health services research in the digital era.

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.

Is the Blood Pressure-Enabled Smartwatch Ready to Drive Precision Medicine? Supporting Findings From a Validation Study

Background

The popular wrist-worn wearables recording a variety of health metrics such as blood pressure (BP) in real time could play a potential role to advance precision medicine, but these devices are often insufficiently validated for their performance to enhance confidence in its use across diverse populations. The accuracy of BP-enabled smartwatch is assessed among the multi-ethnic Malaysians, and findings is discussed in comparison with conventional automated upper-arm BP device.

Methods

Validation procedures followed the guidelines by the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO) Universal Standard (ISO 81060-2:2018). Quota sampling was employed to obtain eligible patients with normal and abnormal BP as per guideline. The measurements of BP were taken at wrist using HUAWEI WATCH D (test BP); and the readings were assessed against reference BP by the mercury sphygmomanometer. Agreement statistics and linear regression analyses were performed.

Results

BP measurements (234 data pairs) from 78 patients that fulfilled AAMI/ESH/ISO protocol were analyzed. The BP readings taken by the HUAWEI WATCH D were comparable to reference BP by sphygmomanometer based on 1) Criterion 1: systolic blood pressure (SBP) = -0.034 (SD 5.24) and diastolic blood pressure (DBP) = -0.65 (SD 4.66) mm Hg; and 2) Criterion 2: SBPs = -0.034 (SD 4.18) and DBPs = -0.65 (SD 3.94) mm Hg. Factors of sociodemographic characteristics, anthropometric measurements, cardiovascular comorbidities, and wrist hair density were not significantly associated with the mean BP differences.

Conclusions

HUAWEI WATCH D fulfilled criteria 1 and 2 of the AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018) guidelines. It can be recommended for clinical use across a wider population. The rich data from real-time BP measurements in concurrent with other health-related parameters recorded by the smartwatch wearable offer opportunities to drive precision medicine in tackling therapeutic inertia by personalizing BP control regimen.

The 2023 wearable photoplethysmography roadmap

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.

scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations

Significance

Monte Carlo (MC) simulations are currently the gold standard in the near-infrared and diffuse correlation spectroscopy (NIRS/DCS) communities for generating light transport paths through tissue. However, realistic and diverse models that capture complex tissue layers are not easily available to all; moreover, manually placing optodes on such models can be tedious and time consuming. Such limitations may hinder the adoption of representative models for basic simulations and the use of these models for large-scale simulations, e.g., for training machine learning algorithms.

Aim

We aim to provide the NIRS/DCS communities with an open-source, user-friendly database of morphologically and optically realistic head models, as well as a succinct software pipeline to prepare these models for mesh-based Monte Carlo simulations of light transport.

Approach

Sixteen anatomical models were created from segmented T1-weighted magnetic resonance imaging (MRI) head scans and converted to tetrahedral mesh volumes. Approximately 800 companion scalp surface locations were distributed on each model, comprising full head coverage. A pipeline was created to place custom source and optical detectors at each location, and guidance is provided on how to use these parameters to set up MC simulations.

Results

The models, head surface locations, and all associated code are freely available under the scatterBrains project on Github.

Conclusions

The NIRS/DCS community benefits from having shared resources for conducting MC simulations on realistic head geometries. We hope this will make MRI-based head models and virtual optode placement easily accessible to all. Contributions to the database are welcome and encouraged.

Non-contact measurement of neck pulses achieved by imaging micro-motions in the neck skin

We report a method and system of micro-motion imaging (µMI) to realize non-contact measurement of neck pulses. The system employs a 16-bit camera to acquire videos of the neck skin, containing reflectance variation caused by the neck pulses. Regional amplitudes and phases of pulse-induced reflection variation are then obtained by applying a lock-in amplification algorithm to the acquired videos. Composite masks are then generated using the raw frame, amplitude and phase maps, which are then used to guide the extraction of carotid pulse (CP) and jugular vein pulse (JVP) waveforms. Experimental results sufficiently demonstrate the feasibility of our method to extract CP and JVP waves. Compared with conventional methods, the proposed strategy works in a non-contact, non-invasive and self-guidance manner without a need for manual identification to operate, which is important for patient compliance and measurement objectivity. Considering the close relationship between neck pulses and cardiovascular diseases, for example, CA stenosis, the proposed µMI system and method may be useful in the development of early screening tools for potential cardiovascular diseases.

Key Considerations When Developing and Implementing Digital Technology for Early Detection of Dementia-Causing Diseases Among Health Care Professionals: Qualitative Study

BACKGROUND

The World Health Organization (WHO) promotes using digital technologies to accelerate global attainment of health and well-being. This has led to a growth in research exploring the use of digital technology to aid early detection and preventative interventions for dementia-causing diseases such as Alzheimer disease. The opinions and perspectives of health care professionals must be incorporated into the development and implementation of technology to promote its successful adoption in clinical practice.

OBJECTIVE

This study aimed to explore health care professionals' perspectives on the key considerations of developing and implementing digital technologies for the early detection of dementia-causing diseases in the National Health Service (NHS).

METHODS

Health care professionals with patient-facing roles in primary or secondary care settings in the NHS were recruited through various web-based NHS clinical networks. Participants were interviewed to explore their experiences of the current dementia diagnostic practices, views on early detection and use of digital technology to aid these practices, and the challenges of implementing such interventions in health care. An inductive thematic analysis approach was applied to identify central concepts and themes in the interviews, allowing the data to determine our themes. A list of central concepts and themes was applied systematically to the whole data set using NVivo (version 1.6.1; QSR International). Using the constant comparison technique, the researchers moved backward and forward between these data and evolving explanations until a fit was made.

RESULTS

Eighteen semistructured interviews were conducted, with 11 primary and 7 secondary care health care professionals. We identified 3 main categories of considerations relevant to health care service users, health care professionals, and the digital health technology itself. Health care professionals recognized the potential of using digital technology to collect real-time data and the possible benefits of detecting dementia-causing diseases earlier if an effective intervention were available. However, some were concerned about postdetection management, questioning the point of an early detection of dementia-causing diseases if an effective intervention cannot be provided and feared this would only lead to increased anxiety in patients. Health care professionals also expressed mixed opinions on who should be screened for early detection. Some suggested it should be available to everyone to mitigate the chance of excluding those who are not in touch with their health care or are digitally excluded. Others were concerned about the resources that would be required to make the technology available to everyone.

CONCLUSIONS

This study highlights the need to design digital health technology in a way that is accessible to all and does not add burden to health care professionals. Further work is needed to ensure inclusive strategies are used in digital research to promote health equity.

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.

Digital health-high tech or high touch?

Digital transformation in medicine refers to the implementation of information technology-driven developments in the healthcare system and their impact on the way we teach, share, and practice medicine. We would like to provide an overview of current developments and opportunities but also of the risks of digital transformation in medicine. Therefore, we examine the possibilities wearables and digital biomarkers provide for early detection and monitoring of diseases and discuss the potential of artificial intelligence applications in medicine. Furthermore, we outline new opportunities offered by telemedicine applications and digital therapeutics, discuss the aspects of social media in healthcare, and provide an outlook on "Health 4.0."

Association of Demographic and Socioeconomic Indicators With the Use of Wearable Devices Among Children

Importance

The use of consumer-grade wearable devices for collecting data for biomedical research may be associated with social determinants of health (SDoHs) linked to people's understanding of and willingness to join and remain engaged in remote health studies.

Objective

To examine whether demographic and socioeconomic indicators are associated with willingness to join a wearable device study and adherence to wearable data collection in children.

Design, Setting, and Participants

This cohort study used wearable device usage data collected from 10 414 participants (aged 11-13 years) at the year-2 follow-up (2018-2020) of the ongoing Adolescent Brain and Cognitive Development (ABCD) Study, performed at 21 sites across the United States. Data were analyzed from November 2021 to July 2022.

Main Outcomes and Measures

The 2 primary outcomes were (1) participant retention in the wearable device substudy and (2) total device wear time during the 21-day observation period. Associations between the primary end points and sociodemographic and economic indicators were examined.

Results

The mean (SD) age of the 10 414 participants was 12.00 (0.72) years, with 5444 (52.3%) male participants. Overall, 1424 participants (13.7%) were Black; 2048 (19.7%), Hispanic; and 5615 (53.9%) White. Substantial differences were observed between the cohort that participated and shared wearable device data (wearable device cohort [WDC]; 7424 participants [71.3%]) compared with those who did not participate or share data (no wearable device cohort [NWDC]; 2900 participants [28.7%]). Black children were significantly underrepresented (-59%) in the WDC (847 [11.4%]) compared with the NWDC (577 [19.3%]; P < .001). In contrast, White children were overrepresented (+132%) in the WDC (4301 [57.9%]) vs the NWDC (1314 [43.9%]; P < .001). Children from low-income households (<$24 999) were significantly underrepresented in WDC (638 [8.6%]) compared with NWDC (492 [16.5%]; P < .001). Overall, Black children were retained for a substantially shorter duration (16 days; 95% CI, 14-17 days) compared with White children (21 days; 95% CI, 21-21 days; P < .001) in the wearable device substudy. In addition, total device wear time during the observation was notably different between Black vs White children (β = -43.00 hours; 95% CI, -55.11 to -30.88 hours; P < .001).

Conclusions and Relevance

In this cohort study, large-scale wearable device data collected from children showed considerable differences between White and Black children in terms of enrollment and daily wear time. While wearable devices provide an opportunity for real-time, high-frequency contextual monitoring of individuals' health, future studies should account for and address considerable representational bias in wearable data collection associated with demographic and SDoH factors.

Methods for the metrological characterization of wearable devices for the measurement of physiological signals: state of the art and future challenges

Wearable devices are rapidly spreading in many different application fields and with diverse measurement accuracy targets. However, data on their metrological characterization are very often missing or obtained with non-standardized methods, hence resulting in barely comparable results. The aim of this review paper is to discuss the existing methods for the metrological characterization of wearable sensors exploited for the measurement of physiological signals, highlighting the room for research still available in this field. Furthermore, as a case study, the authors report a customized method they have tuned for the validation of wireless electrocardiographic monitors. The literature provides a plethora of test/validation procedures, but there is no shared consensus on test parameters (e.g. test population size, test protocol, output parameters of validation procedure, etc.); on the other hand, manufacturers rarely provide measurement accuracy values and, even when they do, the test protocol and data processing pipelines are generally not disclosed. Given the increasing interest and demand of wearable sensors also for medical and diagnostic purposes, the metrological performance of such devices should be always considered, to be able to adequately interpret the results and always deliver them associated with the related measurement accuracy.•The sensor metrological performance should be always properly considered.•There are no standard methods for wearable sensors metrological characterization.•It is important to define rigorous test protocols, easily tunable for specific target applications.

Photoplethysmography-new applications for an old technology: a sleep technology review

Education is integral to the American Academy of Sleep Medicine (AASM) mission. The AASM Emerging Technology Committee identified an important and evolving piece of technology that is present in many of the consumer and clinical technologies that we review on the AASM #SleepTechnology (https://aasm.org/consumer-clinical-sleep-technology/) resource-photoplethysmography. As more patients with sleep tracking devices ask clinicians to view their data, it is important for sleep providers to have a general understanding of the technology, its sensors, how it works, targeted users, evidence for the claimed uses, and its strengths and weaknesses. The focus in this review is photoplethysmography-a sensor type used in the familiar pulse oximeter that is being developed for additional utilities and data outputs in both consumer and clinical sleep technologies.

CITATION

Ryals S, Chang A, Schutte-Rodin S, et al. Photoplethysmography-new applications for an old technology: a sleep technology review. J Clin Sleep Med. 2023;19(1):189-195.

Wearables in Cardiovascular Disease

Wearable devices stand to revolutionize the way healthcare is delivered. From consumer devices that provide general health information and screen for medical conditions to medical-grade devices that allow collection of larger datasets that include multiple modalities, wearables have a myriad of potential uses, especially in cardiovascular disorders. In this review, we summarize the underlying technologies employed in these devices and discuss the regulatory and economic aspects of such devices as well as the future implications of their use.

Modeling Energy Aware Photoplethysmography for Personalized Healthcare Applications

The rise of wearable health monitoring has largely incorporated photoplethysmography (PPG), an optical sensing modality, to determine heart rate and blood oxygen saturation metrics by reflecting light through a user's skin. Due to its optical nature, this sensing method is strongly impacted by the skin type, body mass index (BMI), and general physiological composition of the user. In the context of self-powering, there is a need for these devices to consume ultra-low power, to not be dependent on batteries and regular charging, enabling continuous monitoring. This paper presents a novel PPG sensing model for both a custom, ultra-low power (ULP) AFE and the Texas Instruments (TI) AFE4404 which is used to demonstrate the design tradeoffs between system power and SNR. The models also incorporate a novel human skin reflectance component to analyze the effect of the user's skin phototype and BMI on these tradeoffs with the goal of demonstrating inclusive, accurate ULP PPG sensing. Measured results on both devices from 23 participants are included to emphasize the limited design space for enabling self-powered, continuous monitoring wearables.

A Multilayer Monte Carlo Analysis of Optical Interactions in Reflectance Neck Photoplethysmography

This paper presents a multilayer Monte Carlo model of a healthy human neck to investigate the light-tissue interaction during different perfusion states within its dermal layer. Whilst there is great interest in advancing wearable technologies for medical applications, and non-invasive techniques like photoplethysmography (PPG) have been studied in detail, research has focused on more conventional body regions like the finger, wrist, and ear. Alternatively, the neck could offer access to additional physiological parameters which other body regions are unsuitable for. The aim of this work was to investigate the effects of several factors that would influence the optimum design of a reflectance PPG sensor for the neck. These included the source-detector separation on the optical path, penetration depth, and light detection efficiency. The results were generated from a static multilayer model in a reflectance mode geometry at two wavelengths, 660 nm and 880 nm, containing different blood volume fractions with a fixed oxygen saturation. Simulations indicated that both wavelengths penetrated similar depths, where optimal source-detector separation should not exceed 3 mm or 2.4 mm, for red and infrared respectively. Within this range, light interrogates the dermal-fat boundary corresponding to the last neck tissue layer positively contributing to a neck PPG acquisition.