Photoplethysmography Sensor Research Articles

A wearable photoplethysmography sensor for non-invasive equine heart rate monitoring

In recent years, advancement in biomedical sensors has led to increasingly accurate and accessible biological vital sign collection in nontraditional and noncontrolled application domains. Despite much progress, the implementation within the veterinary medicine field is still limited, which, in part, is due to a lack of rapid, robust, and easy-to-use sensors. To tackle this challenge this work presents a compact and wearable photoplethysmography (PPG) sensor for monitoring equine heart rates (HRs) from the ventral midline near the base of the tail. The PPG waveforms were robustly collected from a group of 50 equine subjects with various age, sex, and breed and then used for HR calculation. The system achieved an accuracy of 94% for HR calculation from the subjects at rest compared to the ground truth HRs acquired from the same subjects by a stethoscope. Statistical analysis on the collected data was conducted to further investigate the robustness of the HR calculations in different age, sex, and breed demographics. This work demonstrates that the PPG-based sensor for HR monitoring shows great potential of being a complementary tool in veterinary medicine for promoting furtherance of the animal health.

Nonlinear features of photoplethysmography signals for Non-invasive blood pressure estimation

ObjectiveContinuous monitoring of blood pressure (BP) plays an essential role in the prognosis and prevention of hypertension and related cardiovascular diseases. Moreover, the ever-increasing demand for portable continuous health monitoring systems coupled with promising capabilities of photoplethysmography (PPG) sensors for developing easy-to-use, portable wearable devices have motivated many researchers toward applying PPG signals for non-invasive health monitoring. Nonlinear nature of BP and proven capability of the Poincaré plot for analyzing dynamic behavior of nonlinear systems motivated us to use this powerful tool for BP estimation. This study aims to explore the dynamical behavior of PPG signals to assist feature extraction for machine-learning (ML) algorithms to estimate BP. We proposed a Poincaré-based feature extraction method for BP estimation with no need to extract precise local points on the PPG signal. MethodsFirst, a Poincaré plot of 10-s segments of the PPG signal was prepared. Then, three distinct time series were retrieved from Poincaré mapping of PPG signals; following this, numerous indices were extracted from the three time series. The F-Test feature selection method was applied to pick the most effective features. Finally, the picked features were fed into different ML algorithms for the estimation of BP. ResultsThe proposed method was validated using a subset of the Medical Information Mart for Intensive Care II (MIMIC-II) database containing ambulatory blood pressure (ABP) and PPG records. The performance evaluation was carried out in terms of mean absolute error (MAE), standard deviation (STD), and Pearson’s correlation coefficient. According to the results, application of the Gaussian process regression (GPR) led to the best performance for both systolic and diastolic BP (0.79 ± 3.08 and 1.38 ± 4.53 mmHg, respectively). Satisfying the criteria for Advancement of Medical Instrumentation (AAMI), it was rated as Grade A for systolic and diastolic BP measurements under terms of British Hypertension Society (BHS) standards, which confirms the efficiency of the Poincaré-based features for BP estimation. ConclusionThe results justify the usefulness of the proposed Poincaré-based features as a powerful tool in BP estimation scenarios.

A computationally efficient algorithm for wearable sleep staging in clinical populations

This study describes a computationally efficient algorithm for 4-class sleep staging based on cardiac activity and body movements. Using an accelerometer to calculate gross body movements and a reflective photoplethysmographic (PPG) sensor to determine interbeat intervals and a corresponding instantaneous heart rate signal, a neural network was trained to classify between wake, combined N1 and N2, N3 and REM sleep in epochs of 30 s. The classifier was validated on a hold-out set by comparing the output against manually scored sleep stages based on polysomnography (PSG). In addition, the execution time was compared with that of a previously developed heart rate variability (HRV) feature-based sleep staging algorithm. With a median epoch-per-epoch κ of 0.638 and accuracy of 77.8% the algorithm achieved an equivalent performance when compared to the previously developed HRV-based approach, but with a 50-times faster execution time. This shows how a neural network, without leveraging any a priori knowledge of the domain, can automatically “discover” a suitable mapping between cardiac activity and body movements, and sleep stages, even in patients with different sleep pathologies. In addition to the high performance, the reduced complexity of the algorithm makes practical implementation feasible, opening up new avenues in sleep diagnostics.

24-HOUR AMBULATORY BLOOD PRESSURE MEASUREMENT USING A PULSE ARRIVAL TIME BASED BLOOD PRESSURE MODEL BY A PROTOTYPE WEARABLE SENSOR

Objective: Methods to enable cuffless blood pressure (BP) have gained widespread interest. If proven to be comparable to standard cuff measurements and more accepted by patients, these methods can improve hypertension care. We investigated accuracy and patient acceptability of a pulse arrival time (PAT) based model using a prototype cuffless device on the chest compared to standard 24-hour ambulatory blood pressure monitoring (24hABPM). Design and method: PAT was calculated using the electrocardiogram (ECG) and photoplethysmography (PPG) sensors incorporated in the chest belt. The model to predict BP from PAT was developed from a general population cohort during isometric exercise induced BP changes. Ninety-four normotensive and hypertensive adults underwent simultaneous 24hABPM with the prototype chest belt sensor and a validated cuff-based oscillometric device on the non-dominant arm. PAT-based BP predictions were compared to reference BPs using 2-minute time windows corresponding to reference measurements. Statistical analyses were performed using Stata® v. 17.0 (Statacorp., Texas, USA) with continuous data presented as means (SD) and compared using paired t-test. Correlation analysis and agreement were evaluated by Bland-Altman plots. Results: Mean age (SD) was 48.1 (14.3) years and 48 % had a prior hypertension diagnosis. Comparisons between reference and PAT-based mean 24-hour, daytime and nighttime BP showed that the PAT-based model generally overestimated BP (Table). The largest difference was seen during nighttime; the mean difference (SD) was 19.6 (22.2) mmHg and 17.0 (12.2) mmHg for systolic BP (SBP) and diastolic BP (DBP). Ninety-five % limits of agreements were [-29.8, 36.0 mmHg] and [-23.9, 63.0 mmHg] for daytime and nighttime SBP. The prototype sensor was reported to be more comfortable and less disturbing during daily activities and sleep compared to the reference device during 24hABPM (Figure). Conclusions: The present study demonstrated that a general PAT-based BP model significantly overestimated 24hABPM in normotensive and hypertensive subjects. The largest discrepancy was observed during nighttime. Although the PAT-based model did not provide accurate measurements of BP, the potential of cuffless BP technology is promising due to patient acceptability.

Driver Stress Detection from Physiological Signals by Virtual Reality Simulator

One of the many areas in which artificial intelligence (AI) techniques are used is the development of systems for the recognition of vital emotions to control human health and safety. This study used biometric sensors in a multimodal approach to capture signals in the recognition of stressful situations. The great advances in technology have allowed the development of portable devices capable of monitoring different physiological measures in an inexpensive, non-invasive, and efficient manner. Virtual reality (VR) has evolved to achieve a realistic immersive experience in different contexts. The combination of AI, signal acquisition devices, and VR makes it possible to generate useful knowledge even in challenging situations in daily life, such as when driving. The main goal of this work is to combine the use of sensors and the possibilities offered by VR for the creation of a system for recognizing stress during different driving situations in a vehicle. We investigated the feasibility of detecting stress in individuals using physiological signals collected using a photoplethysmography (PPG) sensor incorporated into a commonly used wristwatch. We developed an immersive environment based on VR to simulate experimental situations and collect information on the user’s reactions through the detection of physiological signals. Data collected through sensors in the VR simulations are taken as input to several models previously trained by machine learning (ML) algorithms to obtain a system that performs driver stress detection and high-precision classification in real time.

Evaluating the Potential of an Oral-Based Bioguard to Estimate Heart Rate Using Photoplethysmography.

The reliable monitoring of heart rate during intense exercise is imperative to effectively manage training loads while providing insights from a healthcare perspective. However, current technologies perform poorly in contact sports settings. This study aims to evaluate the best approach for heart rate tracking using photoplethysmography sensors embedded into an instrumented mouthguard (iMG). Seven adults wore iMGs and a reference heart rate monitor. Several sensor placements, light sources and signal intensities were explored for the iMG. A novel metric related to the positioning of the sensor in the gum was introduced. The error between the iMG heart rate and the reference data was assessed to obtain insights into the effect of specific iMG configurations on measurement errors. Signal intensity was found to be the most important variable for error prediction, followed by the sensor light source, sensor placement and positioning. A generalized linear model combining an infrared light source, at an intensity of 5.08 mA, and a frontal placement high in the gum area resulted in a heart rate minimum error of 16.33%. This research shows promising preliminary results for the use of oral-based heart rate monitoring, but highlights the need for the careful consideration of sensor configurations within these systems.

Towards Nonintrusive and Secure Mobile Two-Factor Authentication on Wearables

Mobile devices are promising to apply two-factor authentication to improve system security. Existing solutions have certain limits of requiring extra user effort, which might seriously affect user experience and delay authentication time. In this paper, we propose PPGPass, a novel mobile two-factor authentication system, which leverages Photoplethysmography (PPG) sensors available in most wrist-worn wearables. PPGPass simultaneously performs a password/pattern/signature authentication and a physiological-based authentication. To realize both nonintrusive and secure, we design a two-stage algorithm to separate clean heartbeat signals from PPG signals contaminated by motion artifacts so that users do not have to deliberately keep their bodies still. In addition, to deal with noncancelable issues when biometrics are compromised, we design a repeatable and non-invertible method to generate cancelable feature templates as alternative credentials. We leverage the great power of Random Forest and Support Vector Data Description to detect adversaries and verify a user's identity. To the best of our knowledge, PPGPass is the first nonintrusive and secure mobile two-factor authentication based on PPG sensors. Extensive experiments demonstrate that PPGPass can achieve the false acceptance rate of 3.11% and the false recognition rate of 3.71%, which confirms its high effectiveness, security, and usability.

Real-Time Evaluation of Time-Domain Pulse Rate Variability Parameters in Different Postures and Breathing Patterns Using Wireless Photoplethysmography Sensor: Towards Remote Healthcare in Low-Resource Communities.

Photoplethysmography (PPG) signals have been widely used in evaluating cardiovascular biomarkers, however, there is a lack of in-depth understanding of the remote usage of this technology and its viability for underdeveloped countries. This study aims to quantitatively evaluate the performance of a low-cost wireless PPG device in detecting ultra-short-term time-domain pulse rate variability (PRV) parameters in different postures and breathing patterns. A total of 30 healthy subjects were recruited. ECG and PPG signals were simultaneously recorded in 3 min using miniaturized wearable sensors. Four heart rate variability (HRV) and PRV parameters were extracted from ECG and PPG signals, respectively, and compared using analysis of variance (ANOVA) or Scheirer-Ray-Hare test with post hoc analysis. In addition, the data loss was calculated as the percentage of missing sampling points. Posture did not present statistical differences across the PRV parameters but a statistical difference between indicators was found. Strong variation was found for the RMSSD indicator in the standing posture. The sitting position in both breathing patterns demonstrated the lowest data loss (1.0 ± 0.6 and 1.0 ± 0.7) and the lowest percentage of different factors for all indicators. The usage of commercial PPG and BLE devices can allow the reliable extraction of the PPG signal and PRV indicators in real time.

The relationship between liver lipase gene polymorphism and the development of endothelial dysfunction in military personnel in extreme climatic conditions

BACKGROUND:The analysis of the association of polymorphism of hepatic lipase gene with vascular wall stiffness in extreme climatic conditions, the development of criteria for the selection and effectiveness of military service in the Arctic zone, depending on the characteristics of the genotype is one of the main tasks of military medicine.
 AIM:The aim is to evaluate the relationship of the polymorphism of theLIPCrs2043085andrs1532085genes with vascular wall stiffness in military personnel in extreme climatic conditions.
 MATERIALS AND METHODS:295 contract servicemen undergoing military service in various climatic and geographical conditions were examined. Participants are divided into three groups: 1stgroup 100 people serving in the Arctic climate zone; 2ndgroup 100 people serving in the temperate climate zone; 3rdgroup 95 people serving in the conditions of the midmountain subtropical zone. The average age of military personnel in all groups was approximately 34 years. All the examined patients were examined, blood pressure and heart rate were measured, regional blood circulation was assessed using the AngioScan-01P device based on the study of the shape of the volumetric pulse wave by a photoplethysmographic sensor, and a molecular genetic study was performed. Genotyping of single-nucleotide variants of theLIPCrs2043085andrs1532085genes was performed using a polymerase chain reaction in real time on an amplifier (RT-PCR) DT-Prime (GC DNA Technology, Russia) using a set of reagents manufactured by the company Syntol (Moscow).
 RESULTS:In servicemen undergoing military service in the Arctic zone, a significant increase in systolic blood pressure, increased vascular stiffness, arterial wall stiffness, and average arterial wall stiffness were revealed. In military personnel undergoing military service in the conditions of the mid-mountain subtropical zone, a significant increase in the stiffness of the artery wall was revealed. On the contrary, high elasticity of the arterial wall has been established in servicemen undergoing military service in a temperate zone. Statistically significant differences in the frequency of occurrence of theLIPSgene (rs2043085) were found in servicemen undergoing military service in various climatic and geographical zones: in the Arctic zone mainly persons with the T/T genotype (up to 53%), in the temperate zone the T/C genotype prevails (up to 43%), in the subtropical zone genotype C/C (up to 40%). The association of the T/T genotype of theLIPSgene (rs2043085) with the stiffness of the vascular wall was established, which corresponds to an excess of the average passport age of the subjects by 67 years, and in the same genotype, according to the type of pulse wave, there is a tendency to increase the stiffness of the artery wall in servicemen aged 34 years with an average military service of 13 years, serving in the Arctic zone for more than 10 years.
 CONCLUSIONS:In the conditions of the Arctic belt, with prolonged exposure (more than 10 years) to adverse environmental factors, the cardiovascular system is depleted, physiological functions are involuted and the body prematurely ages in the form of hypertonic vascular reactions with the progression of excessive vascular stiffness, especially in individuals with theLIPSgene genotype T/T (rs2043085).

MEASURING OSTEOARTHRITIS KNEE NOCICEPTION USING PHYSIOLOGICAL AND MOVEMENT RESPONSES AND A DEFINED THERMAL STIMULUS: A PROOF OF CONCEPT STUDY

Mechanical loading of joints with osteoarthritis (OA) results in pain-related functional impairment, altered joint mechanics and physiological nociceptor interactions leading to an experience of pain. However, the current tools to measure this are largely patient reported subjective impressions of a nociceptive impact. A direct measure of nociception may offer a more objective indicator. Specifically, movement-induced physiological responses to nociception may offer a useful way to monitor knee OA. In this study, we gathered preliminary data on healthy volunteers to analyse whether integrated biomechanical and physiological sensor datasets could display linked and quantifiable information to a nociceptive stimulus.Following ethical approval, 15 healthy volunteers completed 5 movement and stationary activities in 2 conditions; a control setting and then repeated with an applied quantified thermal pain stimulus to their right knee. An inertial measurement unit (IMU) and an electromyography (EMG) lower body marker set were tested and integrated with ground reaction force (GRF) data collection. Galvanic skin response electrodes for skin temperature and conductivity and photoplethysmography (PPG) sensors were manually timestamped to the integrated system.Pilot data showed EMG, GRF and IMU fluctuations within 0.5 seconds of each other in response to a thermal trigger. Preliminary analysis on the 15 participants tested has shown skin conductance, PPG, EMG, GRFs, joint angles and kinematics with varying increases and fluctuations during the thermal condition in comparison to the control condition.Preliminary results suggest physiological and biomechanical data outputs can be linked and identified in response to a defined nociceptive stimulus. Study data is currently founded on healthy volunteers as a proof-of-concept. Further exploratory statistical and sensor readout pattern analysis, alongside early and late-stage OA patient data collection, can provide the information for potential development of wearable nociceptive sensors to measure disease progression and treatment effectiveness.

Ultrathin, soft, radiative cooling interfaces for advanced thermal management in skin electronics

Thermal management plays a notable role in electronics, especially for the emerging wearable and skin electronics, as the level of integration, multifunction, and miniaturization of such electronics is determined by thermal management. Here, we report a generic thermal management strategy by using an ultrathin, soft, radiative-cooling interface (USRI), which allows cooling down the temperature in skin electronics through both radiative and nonradiative heat transfer, achieving temperature reduction greater than 56°C. The light and intrinsically flexible nature of the USRI enables its use as a conformable sealing layer and hence can be readily integrated with skin electronics. Demonstrations include passive cooling down of Joule heat for flexible circuits, improving working efficiency for epidermal electronics, and stabling performance outputs for skin-interfaced wireless photoplethysmography sensors. These results offer an alternative pathway toward achieving effective thermal management in advanced skin-interfaced electronics for multifunctionally and wirelessly operated health care monitoring.

Advances in Polymethine Dyes for Near‐Infrared Organic Photodiodes†

Comprehensive SummaryNear‐infrared organic photodiodes (NIR OPDs) have tremendous potential in industrial, military, and scientific applications, due to their unique features of lightweight, low toxicity, high structural flexibility, cooling‐system‐free, etc. However, the overall performance of currently available NIR OPDs still lags behind the commercial inorganic photodetectors, ascribed to the critical challenge of realizing organic semiconductors with sufficiently low optical bandgap and excellent optoelectronic properties simultaneously. Among various types of NIR‐absorbing organic semiconductors, polymethine dyes not only possess advantages of simple synthesis and structural diversity, but also show fascinating optical and aggregation features in the solid state, making them attractive material candidates for NIR OPDs. In this review, after a brief introduction of NIR OPDs and polymethine dyes, we comprehensively summarize the advances of polymethine dyes for broadband and narrowband NIR OPDs, and further introduce their applications in all‐organic optical upconversion devices and photoplethysmography sensors. In particular, the relationship between the chemical structure and the aggregation behaviors of polymethine dyes and the device performance is carefully discussed, providing some important molecular insights for developing high performance NIR OPDs.

Investigation of Optimal Light Source Wavelength for Cuffless Blood Pressure Estimation Using a Single Photoplethysmography Sensor.

Routine blood pressure measurement is important for the early detection of various diseases. Recently, cuffless blood pressure estimation methods that do not require cuff pressurization have attracted attention. In this study, we investigated the effect of the light source wavelength on the accuracy of blood pressure estimation using only two physiological indices that can be calculated with photoplethysmography alone, namely, heart rate and modified normalized pulse volume. Using a newly developed photoplethysmography sensor that can simultaneously measure photoplethysmograms at four wavelengths, we evaluated its estimation accuracy for systolic blood pressure, diastolic blood pressure, and mean arterial pressure against a standard cuff sphygmomanometer. Mental stress tasks were used to alter the blood pressure of 14 participants, and multiple linear regression analysis showed the best light sources to be near-infrared for systolic blood pressure and blue for both diastolic blood pressure and mean arterial pressure. The importance of the light source wavelength for the photoplethysmogram in cuffless blood pressure estimation was clarified.

MP27-13 PERIPHERAL NEUROMODULATION OF VAGINAL BLOOD FLOW: A POTENTIAL TREATMENT FOR FEMALE SEXUAL DYSFUNCTION

You have accessJournal of UrologyCME1 Apr 2023MP27-13 PERIPHERAL NEUROMODULATION OF VAGINAL BLOOD FLOW: A POTENTIAL TREATMENT FOR FEMALE SEXUAL DYSFUNCTION Priyanka Gupta, Elizabeth Bottorff, Patricia Maymi-Castrodad, Mackenzie Moore, Giulia Lane, Gianna Rodriguez, and Tim Bruns Priyanka GuptaPriyanka Gupta More articles by this author , Elizabeth BottorffElizabeth Bottorff More articles by this author , Patricia Maymi-CastrodadPatricia Maymi-Castrodad More articles by this author , Mackenzie MooreMackenzie Moore More articles by this author , Giulia LaneGiulia Lane More articles by this author , Gianna RodriguezGianna Rodriguez More articles by this author , and Tim BrunsTim Bruns More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003255.13AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Female sexual dysfunction (FSD) is a potentially life altering condition that impacts an estimated 40% of women. Unfortunately, the few treatment options available have limited success due to their high incidence of adverse events and inability to improve subjective arousal. One potential treatment option, peripheral neuromodulation, has been successful in improving female sexual function index scores. However, the underlying mechanisms of how neuromodulation improves FSD are still largely unknown. We hypothesize that improvements in FSD symptoms are due to improvements in genital hemodynamics. METHODS: We developed a clinical study to investigate changes in vaginal blood flow (VBF) in response to dorsal genital nerve (DGN) and tibial nerve stimulation in three cohorts of women: healthy controls, women with FSD, and women with spinal cord injury (SCI). Incorporating women with SCI allows us to investigate which neural pathways contribute to genital sexual arousal. Each participant attends two study visits: one for each nerve target, randomly ordered. At each visit, a vaginal photoplethysmography (VPP) sensor is used to measure blood flow during a 5-minute baseline, 20 minutes of nerve stimulation, and a 5-minute washout period. The VPP signals are filtered in the neurogenic energy frequency spectrum (0.76 – 0.20 Hz) for analysis. RESULTS: Seven out of eight participants reported genital sensations due to nerve stimulation, three of whom have SCI. One participant with a complete SCI had increases in their VPP neurogenic energy during dorsal genital nerve stimulation (Figure 1). An animal study is being planned to investigate the VBF response observed in complete SCI. CONCLUSIONS: This work provides further support for neuromodulation as a treatment for neurogenic and non-neurogenic FSD. Source of Funding: Craig H. Neilsen Foundation and International Society for the Study of Women’s Sexual Health © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e367 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Priyanka Gupta More articles by this author Elizabeth Bottorff More articles by this author Patricia Maymi-Castrodad More articles by this author Mackenzie Moore More articles by this author Giulia Lane More articles by this author Gianna Rodriguez More articles by this author Tim Bruns More articles by this author Expand All Advertisement PDF downloadLoading ...

100 Long-Distance Triathlons in 100 Days: A Case Study on Ultraendurance, Biomarkers, and Physiological Outcomes.

This study aims to describe and analyze this single athlete's performance, physiological biomarkers, and sleep parameters throughout the 100LDT. An ultraendurance athlete completed an LDT (2.4-mile swim, 112-mile bike ride, and 26.2-mile marathon) each day for 100 consecutive days. Physical work, physiological biomarkers, and sleep parameters were recorded each night using a wrist-worn photoplethysmographic sensor. Clinical exercise tests were performed before and after the 100LDT. Time-series analysis assessed changes in biomarkers and sleep parameters across the 100LDT, and cross-correlations considered the associations between exercise performance and physiological metrics at varying time lags. The swim and cycling performances varied across the 100LDT, while the run was relatively stable. Resting heart rate, heart-rate variability, oxygen saturation, sleep score, light sleep, sleep efficiency, and sleep duration were all best characterized by cubic models. Additional post hoc subanalyses suggest that the first half of the 100LDT most influenced these dynamics. The 100LDT resulted in nonlinear alterations to physiological metrics. This world record was a unique event but allows valuable insights into the limits of human endurance performance.

A Pixelated Monolithic CMOS PPG Sensor for Spatial Feature Acquisition

This article presents a pixelated monolithic CMOS photoplethysmography (PPG) sensor. The spiking neural network (SNN)-inspired architecture, which includes an unbiased photodiode (PD)-based light-to-digital converter (LDC), efficiently converts spatial features of PPG signals to multiple pixelated outputs. The sensor consists of 144 light-sensing neurons (LSNs) and simultaneously generates 1 b 12 row/12 column-wise pixelated outputs. The spatial features of the PPG signals are thoroughly studied with measurement results. Moreover, ambient light canceling with independent component analysis (ICA) is demonstrated as a key application of the proposed sensor. The sensor chip achieves 114 dB dynamic range while consuming 23.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $</tex-math> </inline-formula> W at 1-V supply voltage.

An Easy-to-Use Hand-to-Hand Impedance-Based Sensor to Obtain Carotid Pulse Arrival Time

Pulse arrival times (PATs) are time intervals between the electrocardiogram (ECG) and an arterial pulse wave (APW) widely used to obtain cuffless blood pressure (BP). Although some distal APWs can be easily measured using, for example, a photoplethysmography (PPG) sensor on a finger, proximal APWs, such as the one of the carotid in the neck, are much more difficult to obtain for unskilled users. To overcome this, we propose an impedance-based sensor using only two electrodes in contact with each upper extremity (one to inject current and one to measure voltage at each hand or wrist), which can measure both ECG and an APW [an impedance plethysmogram, (IPG)] to obtain the PAT. Since the injected current flows from hand to hand across the upper torso, we hypothesize that the measured IPG should be sensitive to the arrival of the APW near the heart and, therefore, that the obtained PAT could be used as a surrogate of a proximal PAT even when measured on the hands. We have verified this by comparing the hand-to-hand impedance PAT obtained with the sensor with a gold-standard proximal PAT obtained in the carotid by tonometry in a cohort of 84 volunteers aged 20–61 years, showing a correlation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${r} =0.90$ </tex-math></inline-formula> between the two. These results support the feasibility of future inclusion of these proximal PAT measurements in easy-to-use devices to obtain cuffless BP or other cardiovascular information with improved performance by nonspecialist users outside clinical settings.

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring.

Wearable cuffless photoplethysmographic blood pressure monitors have garnered widespread attention in recent years; however, the long-term performance values of these devices are questionable. Most cuffless blood pressure monitors require initial baseline calibration and regular recalibrations with a cuffed blood pressure monitor to ensure accurate blood pressure estimation, and their estimation accuracy may vary over time if left uncalibrated. Therefore, this study assessed the accuracy and long-term performance of an upper-arm, cuffless photoplethysmographic blood pressure monitor according to the ISO 81060-2 standard. This device was based on a nonlinear machine-learning model architecture with a fine-tuning optimized method. The blood pressure measurement protocol followed a validation procedure according to the standard, with an additional four weekly blood pressure measurements over a 1-month period, to assess the long-term performance values of the upper-arm, cuffless photoplethysmographic blood pressure monitor. The results showed that the photoplethysmographic signals obtained from the upper arm had better qualities when compared with those measured from the wrist. When compared with the cuffed blood pressure monitor, the means ± standard deviations of the difference in BP at week 1 (baseline) were -1.36 ± 7.24 and -2.11 ± 5.71 mmHg for systolic and diastolic blood pressure, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg and met the second criterion of a systolic blood pressure ≤ 6.89 mmHg and a diastolic blood pressure ≤ 6.84 mmHg. The differences in the uncalibrated blood pressure values between the test and reference blood pressure monitors measured from week 2 to week 5 remained stable and met both criteria 1 and 2 of the ISO 81060-2 standard. The upper-arm, cuffless photoplethysmographic blood pressure monitor in this study generated high-quality photoplethysmographic signals with satisfactory accuracy at both initial calibration and 1-month follow-ups. This device could be a convenient and practical tool to continuously measure blood pressure over long periods of time.

SwimmerNET: Underwater 2D Swimmer Pose Estimation Exploiting Fully Convolutional Neural Networks.

Professional swimming coaches make use of videos to evaluate their athletes' performances. Specifically, the videos are manually analyzed in order to observe the movements of all parts of the swimmer's body during the exercise and to give indications for improving swimming technique. This operation is time-consuming, laborious and error prone. In recent years, alternative technologies have been introduced in the literature, but they still have severe limitations that make their correct and effective use impossible. In fact, the currently available techniques based on image analysis only apply to certain swimming styles; moreover, they are strongly influenced by disturbing elements (i.e., the presence of bubbles, splashes and reflections), resulting in poor measurement accuracy. The use of wearable sensors (accelerometers or photoplethysmographic sensors) or optical markers, although they can guarantee high reliability and accuracy, disturb the performance of the athletes, who tend to dislike these solutions. In this work we introduce swimmerNET, a new marker-less 2D swimmer pose estimation approach based on the combined use of computer vision algorithms and fully convolutional neural networks. By using a single 8 Mpixel wide-angle camera, the proposed system is able to estimate the pose of a swimmer during exercise while guaranteeing adequate measurement accuracy. The method has been successfully tested on several athletes (i.e., different physical characteristics and different swimming technique), obtaining an average error and a standard deviation (worst case scenario for the dataset analyzed) of approximately 1 mm and 10 mm, respectively.

A System Based on Photoplethysmography and Photobiomodulation for Autonomic Nervous System Measurement and Adjustment.

(1) Background: The imbalance of the autonomic nervous system (ANS) is common worldwide. Many people have high tension when the sympathetic nervous system is hyperactive or low attention when the parasympathetic nervous system is hyperactive. To improve autonomic imbalance, a feasible and integrated system was proposed to measure and affect the ANS status. (2) Methods: The proposed system consists of a signal-processing module, an LED stimulation module, a photoplethysmography (PPG) sensor and an LCD display. The heart rate variability (HRV) and ANS status can be analyzed from PPG data. To confirm HRV analysis from PPG data, an electrocardiogram (ECG) device was also used to measure HRV. Additionally, photobiomodulation (PBM) was used to affect the ANS status, and two acupuncture points (Neiguan (PC6) and Shenmen (HT7)) were stimulated with different frequencies (10 Hz and 40 Hz) of PBM. (3) Results: Two subjects were tested with the developed system. HRV metrics were discussed in the time domain and frequency domain. HRV metrics have a similar change trend on PPG and ECG signals. In addition, the SDNN was increased, and the parasympathetic nervous system (PNS: HF (%)) was enhanced with a 10 Hz pulse rate stimulation at the Neiguan acupoint (PC6). Furthermore, the SDNN was increased, and the sympathetic nervous system (SNS: LF (%)) was enhanced with a 40 Hz pulse rate stimulation at the Shenmen (HT7) acupoint. (4) Conclusion: A prototype to measure and affect the ANS was proposed, and the functions were feasible. The test results show that stimulating the Neiguan (PC6) acupoint can inhibit the SNS. In contrast, stimulating the Shenmen (HT7) acupoint can activate the SNS. However, more experiments must be conducted to confirm the effect by choosing different pulse rates, dosages and acupoints.