Green PPG Research Articles

Impact of optical wavelength on the reliability of photoplethysmography-based heart rate measurements outside of controlled laboratory environments

Introduction
 The effectiveness of heart rate (HR) measurements via photoplethysmography (PPG) depends on the wavelength of light used. Typical PPG sensors use green, red, or infrared light, each penetrating the skin to different depths (Ray et al., 2021). Here, we present a comparative analysis of the reliability of HR measurements using these wavelengths.
 Methods
 Our study collected a dataset of 16 participants, each wearing four PPG sensing devices placed at the forehead, sternum, ankle (supramalleolar), and wrist. Each device continuously recorded reflective PPG signals, whereas the device at the sternum additionally captured the Lead I ECG for reference. During the 13 hours of capture, participants went on an outdoor trip from downtown Zurich to the Jungfraujoch railway station at 3,460 m above sea level in the mountains. PPG measurements were obtained using a state-of-the-art MAX86141 optical analog front-end (AFE) coupled with an illumination module of red, green, and infrared LEDs (SFH7072), along with two photodiodes. The ECG recording was resolved by a biopotential AFE (MAX30003), affixed on the chest with gel electrodes. All devices were synchronized by aligning recorded signals post-hoc (33ms accuracy, Meier & Holz, 2023). The HR was extracted from the ECG via time-domain peak detection and a quotient filter. HR was separately derived from each PPG signal, both by time-domain peak detection and frequency-domain analysis. The HR was computed every 5 seconds for a window of 30 seconds. For comparing wavelengths, measurements were considered if at least one wavelength yielded HR with less than 10% error which corresponds to 95,000 HR measurements across the whole dataset.
 Results
 HR derived from green PPG was most accurate (median error of 3.8%), followed by infrared (7.2%) and red PPG (9.1%). Given participants activity and movement throughout the 13 hours of capture, calculating HR from green PPG was most accurate 64.2% of the time compared to infrared (21.8%) and red PPG (15.2%). The latter cases, infrared and red PPG resulting in more accurate HR, occurred during periods of moderate and high motion.
 Discussion/Conclusion
 The results indicate that wearable sensors that derive HR from green light PPG can improve their calculations by incorporating additional wavelengths. Since HR based on green light PPG is accurate at rest, PPG using infrared and red would be most beneficial during periods of moderate and increased motion. This finding demonstrates the suitability of infrared and red PPG beyond pulse oxygenation measurements (SpO2). Future work should investigate methods to optimally combine multi-wavelength PPG into a single HR calculation.
 References
 Meier, M., & Holz, C. (2023). BMAR: Barometric and Motion-based Alignment and Refinement for offline signal synchronization across devices. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 7(2), Article 69. https://doi.org/10.1145/3596268
 Ray, D., Collins, T., Woolley, S., & Ponnapalli, P. (2021). A review of wearable multi-wavelength photoplethysmography. IEEE Reviews in Biomedical Engineering, 16, 136-1551. https://doi.org/10.1109/rbme.2021.3121476

Non-invasive assessment of sublingual microcirculation using flow derived from green light PPG: evaluation and reference values.

The study of sublingual microcirculation offers valuable insights into vascular changes and overcomes some limitations of peripheral microcirculation assessment. Videomicroscopy and pulse oximetry have been used to assess microcirculation, providing insights into organ perfusion beyond macrohemodynamics parameters. However, both techniques have important limitations that preclude their use in clinical practice. To address this, we propose a non-invasive approach using photoplethysmography (PPG) to assess microcirculation. Two experiments were performed on different samples of 31 subjects. First, multi-wavelength, finger PPG signals were compared before and while applying pressure on the sensor to determine if PPG signals could detect changes in peripheral microcirculation. For the second experiment, PPG signals were acquired from the ventral region of the tongue, aiming to assess the microcirculation through features calculated from the PPG signal and its first derivative. In experiment 1, 13 out of 15 features extracted from green PPG signals showed significant differences () before and while pressure was applied to the sensor, suggesting that green light could detect flow distortion in superficial capillaries. In experiment 2, 15 features showed potential application of PPG signal for sublingual microcirculation assessment. The PPG signal and its first derivative have the potential to effectively assess microcirculation when measured from the fingertip and the tongue. The assessment of sublingual microcirculation was done through the extraction of 15 features from the green PPG signal and its first derivative. Future studies are needed to standardize and gain a deeper understanding of the evaluated features.

An Adaptive Filter Based Motion Artifact Cancellation Technique Using Multi-Wavelength PPG for Accurate HR Estimation.

This article presents a motion artifact (MA) cancellation technique for accurate photoplethysmography (PPG)-based heart rate (HR) estimation. The MA is canceled using two PPG signals, measured with closely placed red and green LEDs. The proposed technique utilizes the characteristics of the two PPG signals: the high correlation in MA and their different AC/DC ratios. These characteristics allow the MA to be canceled by an adaptive filter while preserving the AC components. In addition, the use of the sign-sign least mean square (SS-LMS) algorithm for the adaptive filter minimizes the hardware resource requirements. To validate the technique, a prototype was implemented and experiments were conducted with six subjects performing three types of movements: walking, running, and squatting. The proposed MA cancellation method significantly reduced the mean absolute error (MAE) in HR estimation, from 9.83 bpm to 1.48 bpm on average, compared to the conventional bandpass filtered green PPG.

Reactive compatibilization of polypropylene grafted with maleic anhydride and styrene, prepared by a mechanochemical method, for a blend system of biodegradable poly(propylene carbonate)/polypropylene spunbond nonwoven slice

Abstract Poly(propylene carbonate) (PPC)/polypropylene (PP) spunbond nonwoven slice has gained more attention, owing to its excellent properties, such as biodegradability, flexibility, biocompatibility, and CO2 utilization. However, the applications of this green material are limited due to the poor thermodynamic incompatibility between PPC and PP. In this paper, PP grafted with maleic anhydride (MAH) and styrene (St) (PP-g-(MAH-co-St)), prepared by a mechanochemical method and having a grafting percentage G MAH = 1.40 %, was used as a compatibilizer to prepare a biodegradable PPC/compatibilizer/PP composite-spunbond nonwoven slice by melt-blending. The effects of compatibilizer content on the tensile strength, elongation at break, melt flow rate, thermal properties, and micro-morphology of PPC/PP-g-(MAH-co-St)/PP were systematically studied. Furthermore, the mechanism of compatibilization of PP-g-(MAH-co-St) in the PPC/PP spunbond nonwoven composite slice is discussed. The results indicated that this green PP-g-(MAH-co-St) exhibited a clear reactive compatibilization effect. Therefore, it can be considered as a good compatibilizer for the biodegradable PPC/PP spunbond nonwoven slice.

Continuous Blood Pressure Monitoring Using Nonpulsatile Photoplethysmographic Components for Low-Frequency Vascular Unloading

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective</i> : Continuous blood pressure (BP) monitoring gives a better understanding of a person’s cardiovascular health status than single BP measurements. The existing measurement techniques are often highly complex and expensive, or suffer from inaccuracies. We propose a simple yet effective technique for continuous blood pressure monitoring. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methods</i> : Our method is based on the finding that the non-pulsatile (DC) component of the photoplethysmograph (PPG) correlates with blood pressure. By keeping the infrared PPG DC component constant by altering the applied external pressure using a feedback mechanism the BP can be measured continuously. This way the pressure read from the pressure sensor follows the mean intra-arterial BP. We call this low-frequency vascular unloading. We propose a method for assessing the measurement error introduced by changes in vasomotor tone. Green PPG was used for the vasomotor compensation method. We packaged the technology to a wearable finger-worn device similar to a pulse oximeter probe. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Results</i> : We measured over 90 minutes of continuous BP data from total of 7 subjects. The subjects were asked to perform different BP altering maneuvers during the measurement. The ability to track BP changes was verified by continuous mean arterial pressure (MAP) readings measured with the reference device (CNSystems CNAP 500) and our device, resulting in correlation of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</i> = 0.894 and (( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mean</i> ± <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SD</i> ) mmHg) of (0.3±4.3) mmHg for mean arterial pressure. Without vasomotor tone compensation the results were with slightly less accurate: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</i> = 0.83, (-1.4±5.1) mmHg. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Conclusion</i> : The proposed technology performed well compared to traditional vascular unloading technique while requiring significantly less complex control logic and no fast-switching pneumatics. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Significance</i> : The proposed technique is simple, yet effective, low-cost solution and it can be constructed from off-the-shelf components and miniaturized into a wearable form factor. The technique has potential in the field of health wearables and remote continuous BP monitoring for personalized health applications.

Dual Wavelength Photoplethysmography Framework for Heart Rate Calculation.

The quality of heart rate (HR) measurements extracted from human photoplethysmography (PPG) signals are known to deteriorate under appreciable human motion. Auxiliary signals, such as accelerometer readings, are usually employed to detect and suppress motion artifacts. A 2019 study by Yifan Zhang and his coinvestigatorsused the noise components extracted from an infrared PPG signal to denoise a green PPG signal from which HR was extracted. Until now, this approach was only tested on "micro-motion" such as finger tapping. In this study, we extend this technique to allow accurate calculation of HR under high-intensity full-body repetitive "macro-motion". Our Dual Wavelength (DWL) framework was tested on PPG data collected from 14 human participants while running on a treadmill. The DWL method showed the following attributes: (1) it performed well under high-intensity full-body repetitive "macro-motion", exhibiting high accuracy in the presence of motion artifacts (as compared to the leading accelerometer-dependent HR calculation techniques TROIKA and JOSS); (2) it used only PPG signals; auxiliary signals such as accelerometer signals were not needed; and (3) it was computationally efficient, hence implementable in wearable devices. DWL yielded a Mean Absolute Error (MAE) of 1.22|0.57 BPM, Mean Absolute Error Percentage (MAEP) of 0.95|0.38%, and performance index (PI) (which is the frequency, in percent, of obtaining an HR estimate that is within ±5 BPM of the HR ground truth) of 95.88|4.9%. Moreover, DWL yielded a short computation period of 3.0|0.3 s to process a 360-second-long run.

SpO2 Measurement: Non-Idealities and Ways to Improve Estimation Accuracy in Wearable Pulse Oximeters

The blood oxygen saturation level (SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) has become one of the vital body parameters for the early detection, monitoring, and tracking of the symptoms of coronavirus diseases 2019 (COVID-19) and is clinically accepted for patient care and diagnostics. Pulse oximetry provides non-invasive SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> monitoring at home and ICUs without the need of a physician/doctor. However, the accuracy of SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> estimation in wearable pulse oximeters remains a challenge due to various non-idealities. We propose a method to improve the estimation accuracy by denoising the red and IR signals, detecting the signal quality, and providing feedback to hardware to adjust the signal chain parameters like LED current or transimpedance amplifier gain and enhance the signal quality. SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> is calculated using the red and infrared photoplethysmogram (PPG) signals acquired from the wrist using Texas Instruments AFE4950EVM. We introduce the green PPG signal as a reference to obtain the window size of the moving average filter for baseline wander removal and as a timing reference for peak and valley detection in the red and infrared PPG signals. We propose the improved peak and valley detection algorithm based on the incremental merge segmentation algorithm. Kurtosis, entropy, and Signal-to-noise ratio (SNR) are used as signal quality parameters, and SNR is further related to the variance in the SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> measurement. A closed-loop implementation is performed to enhance signal quality based on the signal quality parameters of the recorded PPG signals. The proposed algorithm aims to estimate SpO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> with a variance of 1% for the pulse oximetry devices.

Comparative Study of Gesture Recognition Based on Accelerometer and Photoplethysmography Sensor for Gesture Interactions in Wearable Devices

With the goal of implementing gesture interaction applications on wearable devices, this paper presents a comparative study on hand gesture recognition based on accelerometer (ACC) and photoplethysmography (PPG) sensors. Research is conducted on 14 hand gestures involving wrist and finger movements under four motion scenarios: sitting, walking, jogging, and running. When the participants perform the hand gestures, four channels of PPG signals and 3D ACC signals are collected. To effectively extract gesture repetitions from the continuous movements, a segmentation method based on PPG signal and motion noise is employed. The experimental results verify that the PPG signal is more suitable for implementing gesture interactions on wearable devices. At first, the signal-to-noise ratio analysis demonstrates that the ACC signals are much more affected by motion noise than the PPG signals. Then, the hand gesture recognition results in the four different motion scenarios demonstrate that the accuracies of both the ACC and PPG signals decrease with the intensity of body movement; however, the decrease of the PPG signals is significantly lower than that of the ACC signals, especially for finger-related gestures. A hand gesture recognition experiment with ratios of the samples between the training set and test set from 1:9 to 8:2 demonstrates that the PPG signal also has advantages in regards to reducing user's training burden. Moreover, this research verifies that the green PPG signal is not the best choice for the implementation of gesture interactions. The research results provide a reliable foundation for promoting the development of gesture-based interactions in wearable devices.

Blue as an Underrated Alternative to Green: Photoplethysmographic Heartbeat Intervals Estimation under Two Temperature Conditions

Since photoplethysmography (PPG) sensors are usually placed on open skin areas, temperature interference can be an issue. Currently, green light is the most widely used in the reflectance PPG for its relatively low artifact susceptibility. However, it has been known that hemoglobin absorption peaks at the blue part of the spectrum. Despite this fact, blue light has received little attention in the PPG field. Blue wavelengths are commonly used in phototherapy. Combining blue light-based treatments with simultaneous blue PPG acquisition could be potentially used in patients monitoring and studying the biological effects of light. Previous studies examining the PPG in blue light compared to other wavelengths employed photodetectors with inherently lower sensitivity to blue, thereby biasing the results. The present study assessed the accuracy of heartbeat intervals (HBIs) estimation from blue and green PPG signals, acquired under baseline and cold temperature conditions. Our PPG system is based on TCS3472 Color Sensor with equal sensitivity to both parts of the light spectrum to ensure unbiased comparison. The accuracy of the HBIs estimates, calculated with five characteristic points (PPG systolic peak, maximum of the first PPG derivative, maximum of the second PPG derivative, minimum of the second PPG derivative, and intersecting tangents) on both PPG signal types, was evaluated based on the electrocardiographic values. The statistical analyses demonstrated that in all cases, the HBIs estimation accuracy of blue PPG was nearly equivalent to the G PPG irrespective of the characteristic point and measurement condition. Therefore, blue PPG can be used for cardiovascular parameter acquisition. This paper is an extension of work originally presented at the 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Blood Pressure Prediction by a Smartphone Sensor using Fully Convolutional Networks.

Heart disease and stroke are the leading causes of death worldwide. High blood pressure greatly increases the risk of heart disease and stroke. Therefore, it is important to control blood pressure (BP) through regular BP monitoring; as such, it is necessary to develop a method to accurately and conveniently predict BP in a variety of settings. In this paper, we propose a method for predicting BP without feature extraction using fully convolutional neural networks (CNNs). We measured single multi-wave photoplethysmography (PPG) signals using a smartphone. To find an effective wavelength of PPG signals for the generation of accurate BP measurements, we investigated the BP prediction performance by changing the combinations of the input PPG signals. Our CNN-based BP predictor yielded the best performance metrics when a green PPG time signal was used in combination with an instantaneous frequency signal. This combination had an overall mean absolute error (MAE) of 5.28 and 4.92 mmHg for systolic and diastolic BP, respectively. Thus, our CNN-based approach achieved comparable results to other approaches that use a single PPG signal.

The Potential of Wearable Limb Ballistocardiogram in Blood Pressure Monitoring via Pulse Transit Time

The goal of this study was to investigate the potential of wearable limb ballistocardiography (BCG) to enable cuff-less blood pressure (BP) monitoring, by investigating the association between wearable limb BCG-based pulse transit time (PTT) and BP. A wearable BCG-based PTT was calculated using the BCG and photoplethysmogram (PPG) signals acquired by a wristband as proximal and distal timing reference (called the wrist PTT). Its efficacy as surrogate of BP was examined in comparison with PTT calculated using the whole-body BCG acquired by a customized weighing scale (scale PTT) as well as pulse arrival time (PAT) using the experimental data collected from 22 young healthy participants under multiple BP-perturbing interventions. The wrist PTT exhibited close association with both diastolic (group average r = 0.79; mean absolute error (MAE) = 5.1 mmHg) and systolic (group average r = 0.81; MAE = 7.6 mmHg) BP. The efficacy of the wrist PTT was superior to scale PTT and PAT for both diastolic and systolic BP. The association was consistent and robust against diverse BP-perturbing interventions. The wrist PTT showed superior association with BP when calculated with green PPG rather than infrared PPG. In sum, wearable limb BCG has the potential to realize convenient cuff-less BP monitoring via PTT.

Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths

Long-term heart rate (HR) monitoring by wrist-worn photoplethysmograph (PPG) sensors enables the assessment of health conditions during daily life with high user comfort. However, PPG signals are vulnerable to motion artifacts (MAs), which significantly affect the accuracy of estimated physiological parameters such as HR. This paper proposes a novel modular algorithm framework for MA removal based on different wavelengths for wrist-worn PPG sensors. The framework uses a green PPG signal for HR monitoring and an infrared PPG signal as the motion reference. The proposed framework includes four main steps: motion detection, motion removal using continuous wavelet transform, approximate HR estimation and signal reconstruction. The proposed algorithm is evaluated against an electrocardiogram (ECG) in terms of HR error for a dataset of 6 healthy subjects performing 21 types of motion. The proposed MA removal method reduced the average error in HR estimation from 4.3, 3.0 and 3.8 bpm to 0.6, 1.0 and 2.1 bpm in periodic, random, and continuous non-periodic motion situations, respectively.

PO-0342 Can Photoplethysmography Be Used To Automate Capillary Refill Time? Preliminary Results From Healthy Children

Background Capillary refill time (CRT) is widely used in paediatrics to assess cardiovascular status, especially during the early phase of shock when skin perfusion is reduced, but is prone to marked variability (Pickard 2011). CRT is used in early warning scores aimed at identifying and quantifying severity of illness and effectiveness of resuscitation efforts (APLS 2011). CRT is one of the most sensitive predictors of dehydration and bacterial infection in children, and it correlates with markers of end organ perfusion (Tibby 1999, Craig 2010). Automating CRT using photoplethysmography (PPG) with a pressure application system may improve its accuracy and reliability. Aim Establish if a green light PPG and a pressure application system could detect an increase in CRT after skin cooling. Methods Healthy children (aged 5–18 years) underwent selective arm cooling as a model of reduced skin blood flow through the microcirculation (Roustit and Cracowski 2013). An automated green light PPG CRT device was attached to their forearm and their arm was then placed into a refrigeration device at 4°C for 20 min. Using 7 min rolling averages, the trough (early phase) and peak (late phase) CRT values were compared. Ethical approval was given. Results Participants (n = 16) demonstrated a significant increase in CRT (as assessed by green PPG) in 15 of the 16 cases (P Conclusions It is feasible to measure changes in the microcirculation of children using an automated device that mimics CRT testing. Further work in clinical settings is needed to establish if this has clinical utility.

A technique based on laser Doppler flowmetry and photoplethysmography for simultaneously monitoring blood flow at different tissue depths

The aim of this study was to validate a non-invasive optical probe for simultaneous blood flow measurement at different vascular depths combining three photoplethysmography (PPG) channels and laser Doppler flowmeter (LDF). Wavelengths of the PPG were near-infrared 810 nm with source-to-detector separation of 10 and 25 mm, and green 560 nm with source-to-detector separation of 4 mm. The probe is intended for clinical studies of pressure ulcer aetiology. The probe was placed over the trapezius muscle, and depths from the skin to the trapezius muscle were measured using ultrasound and varied between 3.8 and 23 mm in the 11 subjects included. A provocation procedure inducing a local enhancement of blood flow in the trapezius muscle was used. Blood flows at rest and post-exercise were compared. It can be concluded that this probe is useful as a tool for discriminating between blood flows at different vascular tissue depths. The vascular depths reached for the different channels in this study were at least 23 mm for the near-infrared PPG channel (source-to-detector separation 25 mm), 10-15 mm for the near-infrared PPG channel (separation 10 mm), and shallower than 4 mm for both the green PPG channel (separation 4 mm) and LDF.