Photo Plethysmography Research Articles

Design of an IoT-enabled wearable device for stress level monitoring

Modern challenges require effective methods for stress monitoring and management, which drive the implementation of innovative solutions. This article presents the development of a wearable device integrated with Internet of Things (IoT) technology, capable of detecting and quantitatively assessing stress levels in real-time. This technology enhances the accuracy of stress evaluation, enabling quick responses and the development of personalized stress management strategies. The device uses a Field-Programmable Gate Array (FPGA) as the main controller and includes nine sensors: Photo plethysmography (MAX30102), electroencephalography (EEG), electrocardiography (ECG), glucose level (GS), electromyography (EMG), temperature (TS), pressure (PS), heart rate (HRS), pulse (PS), and galvanic skin response (GSR). These sensors measure physiological parameters such as heart rate, skin conductance, and breathing rate, which are associated with stress. The collected data is transmitted via Wi-Fi to the Firebase platform. The article also discusses the benefits of IoT-enabled wearable devices, their versatility for use in various environments such as offices, educational institutions, and healthcare settings, where stress management plays a critical role. Continuous monitoring allows users to track stress levels and take timely actions to improve their well-being. Experimental data shows that the device achieves 85% accuracy in measuring heart rate and breathing. This device can be valuable in both everyday life and professional fields, including medicine, education, and work environments, where stress control is crucial for health and productivity).

Long-Term 10 Years Results of Endovenous Laser Ablation for Chronic Venous Disease: Clinical and Digital Photo Plethysmography Evaluation

Long-Term 10 Years Results of Endovenous Laser Ablation for Chronic Venous Disease: Clinical and Digital Photo Plethysmography Evaluation

Pulse transmission time and amplitude of digital pulse wave determined by fingertip plethysmography as a surrogate marker of brachial artery flowmediated dilatation.

To assess the changes in blood vessel stiffness and digital pulse wave amplitude because of flowmediated dilatation, and to explore how these two variables change when endothelial dysfunction is experimentally induced. The experimental study was conducted at the departments of physiology at the College of Medicine, Mustansiriyah University, and the College of Medicine, Al-Iraqia University, Baghdad, Iraq, from October 14, 2021, to May 31, 2022, and comprised healthy young males who were subjected to the flow-mediated dilatation technique on the left brachial artery. Pulse transit time and the amplitude of the digital pulse wave were measured during reactive hyperaemia for 2.5 minutes from the left middle finger using a piezoelectric pressure sensor and a simultaneous Lead I electrocardiogram. Endothelial dysfunction (ED) was induced by oscillatory and retrograde shear rates. The correlation between variables was calculated in Excel running on the Windows operating system. There were 10 second-year medical students with mean age 22±0 years and mean body mass index 25.7±4.8kg/m2. During reactive hyperaemia, pulse transit time was significantly increased by 3-5% in both normal endothelium and experimentally induced endothelial dysfunction relative to the pre-occluded artery, and the difference was not significant (p>0.05). Digital pulse wave amplitude increased significantly in normal endothelium relative to the pre-occluded artery (p<0.05), but not in experimentally-induced endothelial dysfunction (p>0.05). The pulse transit time and digital pulse wave amplitudes of the photo plethysmography signal may be used to detect changes in vessel wall diameter and tone throughout the reactive hyperaemia process. Digital pulse wave amplitude was better able to detect experimentally-induced endothelial dysfunction, as assessed by the flowmediated dilatation protocol, than pulse transit time.

Health monitoring system using ECG and PPG techniques

The demand for portable health monitoring systems has grown rapidly in recent years due to the increasing prevalence of chronic diseases and the need for continuous health monitoring. This article introduces the development and implementation of a portable health monitoring system using photo plethysmography (PPG) and electrocardiogram (ECG) technologies. The system integrates the Node MCU ESP8266 microcontroller, AD8232 ECG sensor, and MAX30100 sensor to measure vital signs such as heart rate and blood oxygen saturation level. The proposed system provides a cost-effective and efficient solution for real-time health monitoring, enabling early detection of abnormalities and timely intervention. The feasibility and performance of the system were proven through experimental tests.

The Effect of 0.1 Hz Blood Flow Oscillations on Microvascular Blood Flow Responses Following Severe Ischemia

Background: We have shown that inducing 10 second (0.1 Hz) oscillations in arterial pressure and blood flow protects against reductions in tissue oxygenation during ischemia, independent of changes in macrovascular blood flow. However, it is unknown whether 0.1 Hz hemodynamic oscillations impacts microvascular function and vasodilatory capacity following severe ischemia. To examine this question, we assessed the reactive hyperemic response following a prolonged peripheral limb ischemia protocol with and without induced 0.1 Hz hemodynamic oscillations. Hypothesis: 0.1 Hz oscillations in blood pressure and blood flow will increase microvascular blood flow, assessed via reactive hyperemia following a 10-min period of ischemia. Methods: Thirteen healthy human participants (6M, 7F; 27.3 ± 4.2 y) completed two experimental protocols separated by ≥48 h. In both conditions, ischemia of the forearm was induced with a pneumatic cuff on the upper arm to decrease brachial artery blood velocity by ~70-80% from baseline. In the oscillation condition (OSC), 0.1 Hz oscillations in mean arterial pressure (MAP) and brachial artery blood flow were induced by inflating and deflating bilateral thigh cuffs every 5-s (10-s cycles; 0.1 Hz) throughout the forearm ischemia period. In the control condition (CON), the thigh cuffs were in place, but were inactive throughout the forearm ischemia period. Beat to beat arterial pressure was measured via finger photo plethysmography, and brachial artery diameter and blood velocity were measured via duplex Doppler ultrasound during baseline, ischemia, and the reperfusion period. The maximum mean brachial artery blood velocity, and 3-min area under the curve (AUC) of mean brachial artery blood velocity were used to determine the reactive hyperemia response. Results: The magnitude of forearm ischemia, indexed by the reduction in brachial artery conductance, was matched between conditions (CON: -74.8 ± 10.4% vs. OSC: -75.6 ± 6.7%, p=0.39). Reactive hyperemia was not different between conditions as indexed by maximum mean brachial artery blood velocity (CON: 36.4 ± 12.4 cm/s vs. OSC: 39.3 ± 11.2 cm/s, p=0.53) or 3-min brachial artery blood velocity AUC (CON: 1495 ± 744 (cm/s)2 vs. OSC: 1596 ± 804 (cm/s)2, p=0.74). Conclusion: Inducing 0.1 Hz hemodynamic oscillations during severe ischemia does not affect microvascular function, indexed by reactive hyperemia following release of the ischemic stimulus. A more direct measure of microvascular blood flow is needed to examine whether 0.1 Hz hemodynamic oscillations improves microvascular perfusion during ischemia. NIH Neurobiology of Aging &amp; Alzheimer’s Disease Training Grant (T32 AG02049; KAD); American Heart Association Transformational Project Award (19TPA34910743; CAR); American Heart Association Predoctoral Fellowship (23PRE1018469; KAD); UNTHSC Physiology and Anatomy Seed Grant 2021 (CAR). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Utilization of Facial PPG Signals as a Novel Source for Blood Pressure Estimation

Hypertension, a prevalent global health concern, necessitates accurate and non-invasive blood pressure estimation techniques for effective monitoring and management. This paper proposes a novel machine learning approach utilizing Photo plethysmography (PPG) signals for precise blood pressure estimation. PPG signals, obtained conveniently through wearable devices, offer valuable physiological information related to cardiovascular activity. Leveraging advanced machine learning algorithms, including deep learning architectures and feature extraction methods, our proposed technique aims to establish a robust model for blood pressure estimation using facial image analysis. The methodology involves preprocessing PPG signals, extracting relevant features, and employing sophisticated machine learning models for regression analysis. The evaluation of this novel approach involves comprehensive experimentation with diverse datasets, ensuring its efficacy across various demographic groups and conditions. Results demonstrate promising accuracy and reliability in estimating blood pressure values, suggesting the potential for practical implementation in healthcare settings. The proposed technique showcases a promising avenue for non-invasive and accessible blood pressure monitoring, contributing significantly to personalized healthcare and continuous health monitoring systems.

Consumer-grade wearable cardiac monitors: What they do well, and what needs work.

Consumer-grade smart devices, including smartwatches and smartphones, are potentially valuable tools in detecting cardiac arrhythmias, particularly atrial fibrillation, and their use is increasing. These devices, which use photoplethys mography, show remarkably high sensitivity and specificity for detection of atrial fibrillation, with implications for stroke prevention and management in at-risk patients. The ability of the devices to detect atrial fibrillation is being compared with single-lead electrocardiography. Physicians will increasingly be asked to interpret data from these nonmedical-grade devices as they become more common. Limitations include high false-positive rates in certain populations and disparities in access.

Effect of duration of hypertension on arterial stiffness

Background: Hypertension is one of the common and prime causes contributing to 18% of deaths globally. Prevalence of essential hypertension increases with age, and individuals with relatively high blood pressure at younger ages are at increased risk for the subsequent complications of hypertension. The morphological and physiological changes in vasculature have been described in the evolution and maintenance of hypertension. Hypertension can increase the risk of cerebral, cardiac, and renal events. Aims and Objectives: (1) To record the arterial stiffness index (SI) and reflection index (RI) in subjects with hypertension and a control group of age-matched normotensives. (2) To compare the above vascular parameters between control and hypertensive subjects. (3) To classify the hypertensive subjects based on the duration of the disease and compare the vascular parameters among them. Materials and Methods: A cross-sectional study on 160 subjects aged between 30 and 60 years was conducted. Institutional ethical committee approval and informed written consent were obtained. They were divided into four groups. Group 1- control group (Healthy subjects), and study group of hypertensives are classified into three groups based on the duration of illness. Arterial stiffness was evaluated by SI and RI, calculated from recording digital volume pulse (DVP). DVP was measured by an instrument known as finger pulse photo plethysmography. Results: The results were analyzed using analysis of variance test and were considered statistically significant with P &lt; 0.05 with respect to arterial stiffness indices compared with the duration of hypertension. Conclusion: This study concludes a strong positive correlation between two indices of arterial stiffness that is the RI and SI values increases with the duration of hypertension.

Evaluating endovenous laser and glue ablation in the treatment of great saphenous vein insufficiency: A 5-year retrospective comparative study

Aim: The use of endovascular thermal and nonthermal methods in the treatment of chronic venous insufficiency has been in practice for over 10 years. The early results of these practices have been published and extensively discussed. Medium and long-term results are now being announced. In our study, we discussed the results of endovenous laser ablation and endovenous glue ablation methods, along with hemodynamic evaluations. Material and Methods: Doppler USG and Digital Photo Plethysmography were used to examine patients with chronic venous insufficiency in the C2-5 group who received endovenous ablation indication. Records of VCSS and CIVIQ-20 were obtained. Measurements were taken at 1, 3, 6, 12, 24, and 60 months. Procedural and post-procedural variables were compared, and the results were obtained for a 5-year period. Results: The demographic profiles of the groups were similar. The duration of the procedure was significantly longer in the EVLA group. Similarly, the pain during the procedure was statistically significantly higher in the EVLA group. Venous refill time and venous half-life time showed a statistically significant improvement in both groups. While there were close to 100% closure rates in both groups during the first 6 months, the rates decreased to 95.2% in EVLA and 93.5% in EVGA by the end of the fifth year. Conclusion: With 5 years of objective and subjective findings, both EVLA and EVGA are effective and reliable methods with their advantages and disadvantages. However, EVGA may be more preferred by patients because it does not require tumescent anesthesia, causes less pain, and has a shorter procedure time.

Harmonic components of photoplethysmography and pathological patterns: A cross-sectional study.

This study aimed to examine whether the 3 harmonic components (HCs) of photoplethysmography (PTG) - total harmonic distortion (THD), harmonic power (HP), and normalized harmonic amplitude (HA) - have aging effects and may serve as an arterial stiffness marker and examine the relationship between HCs and clinical severity of pathological patterns. This study had a retrospective chart review design, and electronic medical records of 173 female patients (age: 38.57 ± 11.64 years) were reviewed. Patients were asked to complete the phlegm, blood stasis (BS), and food retention (FR) pattern questionnaires and underwent PTG and the second derivative of PTG measurements. THD, HP, and HA data were extracted till the 12th HCs from the raw PTG data. THD and HA had an aging effect (β: -0.179 to -0.278) and were related to b/a (r: -02.76 to -0.455) and d/a (r: 0.265-0.360) of the second derivative of PTG. In the younger group (≤33 years), HP and HA were positively correlated with phlegm, BS, and FR patterns (r: 0.257-0.370), while HP was positively correlated with the FR pattern (r: 0.278-0.315) in the middle age group (34-45 years). In the older group (≥46 years), HP and HA were positively or negatively correlated with the phlegm pattern (r: ±0.263 to ±0.440). HCs may serve as an arterial stiffness marker, and may be partially related to phlegm, BS, and FR patterns. Aging effect needs to be considered when utilizing HCs as an indicator of phlegm, BS, and FR patterns.

A Comparative Accuracy Study of Touch-based Non-invasive Blood Pressure Feature of Device- H360

Background: To take blood pressure (BP) measurements repeatedly is beneficial for managing the control of hypotension and hypertension. Now present readings depend on cuff-based technology. This study compared blood pressure readings taken with new device without cuff photo plethysmography – PPG with a typical mercury-based sphygmomanometer apparatus.Purpose:A comparative accuracy study of the touch-based non-invasive blood pressure (NIBP) feature of device H360 compared with a mercury-based sphygmomanometer.Material and method: The study was conducted among 95 participants (Above 18 years) at Apex Heart Institute, Ahmedabad from 08th December 2022 to 07th January 2023. We concluded the study on three major factors like age, gender, and health status of participants with hypertensive (n=12), hypotensive (n=18) and normotensive (n=65). Hypotensive and normotensive).Results: According to our observations, the results of the study revealed substantial variations between the three groups in terms of the standard deviation (STD), mean value of systolic blood pressure (SBP) and diastolic blood pressure (DBP), as measured by both the H360 and the mercury sphygmomanometer work on the principle that measures blood pressure by constricting the brachial artery with an inflatable cuff. The cuff is inflated until blood flow stops, then slowly deflated until a tapping sound is heard, indicating blood flow resumption. The pressure at which the sound is heard is the systolic blood pressure, while the pressure at which it disappears is the diastolic blood pressure. The mean values of SBP and DBP were highest in the hypertensive group, followed by the normotensive group, and lowest in the hypotensive group.Conclusion: The study concluded that the device H360 device and mercury sphygmomanometer were effective in measuring blood pressure in hypertensive, hypotensive, and normotensive individuals. However, the H360 showed better accuracy and consistency in measuring blood pressure with a mercury sphygmomanometer.

Heartbeat and Respiration Rate Prediction Using Combined Photoplethysmography and Ballisto Cardiography

Owing to the recent trends in remote health monitoring, real-time applications for measuring Heartbeat Rate and Respiration Rate (HARR) from video signals are growing rapidly. Photo Plethysmo Graphy (PPG) is a method that is operated by estimating the infinitesimal change in color of the human face, rigid motion of facial skin and head parts, etc. Ballisto Cardiography (BCG) is a nonsurgical tool for obtaining a graphical depiction of the human body’s heartbeat by inducing repetitive movements found in the heart pulses. The resilience against motion artifacts induced by luminance fluctuation and the patient’s mobility variation is the major difficulty faced while processing the real-time video signals. In this research, a video-based HARR measuring framework is proposed based on combined PPG and BCG. Here, the noise from the input video signals is removed by using an Adaptive Kalman filter (AKF). Three different algorithms are used for estimating the HARR from the noise-free input signals. Initially, the noise-free signals are subjected to Modified Adaptive Fourier Decomposition (MAFD) and then to Enhanced Hilbert vibration Decomposition (EHVD) and finally to Improved Variation mode Decomposition (IVMD) for attaining three various results of HARR. The obtained values are compared with each other and found that the EHVD is showing better results when compared with all the other methods.

Pseudo-V1 ECG lead recording with quality smartwatches and medical interpretation may be necessary for timely and accurate remote detection of atrial flutter/fibrillation

Abstract Background Remote rhythm monitoring with wearable devices is increasingly used especially for early detection of atrial fibrillation/flutter (AF/Afl), being the access to hospital discouraged, especially for frail elderly patients, due to the burden and risk of COVID-19 pandemic. Whereas devices using photo plethysmography (PPG) may misinterpret as AF pulse irregularities due to extrasystoles, patient-directed recording of a single (usually wrist-to-wrist) lead ECG (LEAD I) with hand-held devices or smartwatches have been developed to increase accuracy in AF detection. However, although recent studies validating such devices single-lead ECG recording have shown high sensitivity and specificity, false negative findings such as those reported here are still possible and must be prevented [1]. Purpose Given previous experience of diagnostic uncertainty or failure of the smartwatch ECG (SW-ECG) LEAD I to detect AF/Afl, we have tested if false negative diagnosis could be avoided by recording in addition at least one right precordial (pseudo-V1) lead analyzed by a trained healthcare professional. Method Over one calendar year observation, five patients with previous history of ablated supraventricular arrhythmias suffering sudden palpitations suspected of paroxysmal AF/Afl were instructed to record with their smartwatch at least one precordial lead in addition to LEAD I, to monitor ECG until the termination of symptoms. The SW-ECG strips were sent by telephone for professional interpretation. Diagnostic accuracy based on LEAD I and pseudo-V1 were independently validated by two cardiologists (diagnostic goldstandard - DGS). Results 22 AF/Afl events occurred. Pharmacological cardioversion to sinus rhythm (SR) was obtained in 64%. 192 ECG strips were transmitted. 43,7% of the strips were automatically classified as “not significant” (or “not valid”). Compared to DGS, out of 108 “valid” strips, correct automatic identification of AF/Afl was obtained in 36,4% with LEAD I, in 33,3% with pseudo V1 and in 54,5% with combined leads, respectively. Interestingly, the SW algorithm has wrongly diagnosed as SR, not only LEAD I, but also 39,4% of pseudo-V1 strips, despite clear-cut evidence of typical flutter waves (Figure 1), when RR intervals were regular due to high degree (e.g., 4:1) A-V block. Conclusions With simple instructions, patients (or their relatives) can easily record an additional precordial (pseudo-V1) SW-ECG lead, that may enhance sensitivity and specificity for remote detection of AF/Afl. However, at present, visual interpretation of SW-ECG by a trained healthcare professional is still needed to guarantee 100% correct diagnosis of AF/Afl, crucial to reduce thromboembolic risk and timely initiate the appropriate treatments. The automatic interpretation of SW's ECG could be improved by appropriate training of a machine learning approach to detect and analyze the atrial waveform provided by an additional pseudo-V1 lead. Funding Acknowledgement Type of funding sources: None.

IoT Based Pulse Oximeter for Remote Health Assessment: Design, Challenges and Futuristic Scope

The Internet of Things (IoT) comprises the networking, computing, and storage with analytics technologies that do wonders in every aspect of human life through its applications and turns their life style as smart as possible. The application of IoT in healthcare domain would transform the medical service to be timely accessible and affordable by all people. The cardiovascular diseases (CVD) are marked as one of the most common cause of death around the world. A research study states that CVD targets the public with age limit of 30 - 60 belongs to developing countries like India in an evidential growth. The continuous monitoring of human heart, which is a fist sized strongest muscle through invasive sensors helps in early detection and anticipating necessary treatment on time. This induces a design of IoT enabled pulse rate monitoring system to continuously track the patient at anywhere and better serve them at any time through any device. The device uses easy pulse sensor and is operated through Raspberry Pi. The effectiveness of the device is analyzed against one of the top brand fingertip pulse oximeter, suggested for home and clinical usage in practice. Further the non-invasive design of pulse oximeter which determines the blood pressure (BP) using electrocardiography (ECG) and photo plethysmography (PPG) sensors.

1-Dimensional Convolutional Neural Network Based Blood Pressure Estimation with Photo plethysmography Signals and Semi-Classical Signal Analysis

In this paper, we propose a 1-Dimensional Convolutional Neural Network (1D-CNN) based Blood Pressure (BP) estimation using Photo plethysmography (PPG) signals and their features obtained through Semi-classical Signal Analysis (SCSA). The procedure of the proposed BP estimation technique is as follows. First, PPG signals are divided into each beat. Then, 9 features are obtained through SCSA for the divided beats. In addition, 5 biometric data are used. The Biometrics data include Heart Rate (HR), age, sex, height, and weight. The total 14 features are used for training and validating the 1D-CNN BP estimation model. After testing three types of 1D-CNNs, the model with the most optimal performance is selected. The selected model structure consists of three convolutional layers and one fully connected layer. The performance is measured by Mean Error (ME) ± Standard Deviation (STD) following the Association for the Advancement of Medical Instrumentation (AAMI) standard. According to the results of the test, Systolic Blood Pressure (SBP) is -2.99±14.48 mmHg and Diastolic Blood Pressure (DBP) is 1.16±9.30 mmHg. Using the proposed technique, blood pressure can be easily predicted using PPG obtained with a non-invasive and cuff-less wearable sensor.

A Novel Approach to the Respiratory Disease Follow-up Based on Plethhysmography Signal Parameters

Aim: The aim of this paper is to present a novel approach for the monitoring of respiratory diseases based on the combined study of heart rate, respiratory rate and Pulse Oximetry (SpO2). Introduction: Since the start of the COVID-19 pandemic, respiratory diseases have increased its worldwide prevalence dramatically. Added to the impact of the pandemic is the already existing situation of a growing prevalence of diseases such as bronchial asthma and Chronic Obstructive Pulmonary Disease (COPD). On the other hand, it is known that the cardiovascular system is overloaded when there are respiratory insufficiencies and this condition can cause severe damage to health. Pulmonology and Cardiology are independent medical specialties that deal with these diseases and often do not cooperate with each other strongly, so a proposal is presented that combines respiratory and cardiovascular variables to deal with this health problem. Methods: A prototype was developed based on the STM32L073CZTx processor controlling the E305654 pulse oximetry module, which on demand delivers SpO2, photo plethysmography signal samples and pulse rate values. A vector was computed, every thirty minutes, to combine the respiratory rate obtained from the Plethysmography Signal (PPG), the mean value of SpO2 and the pulse rate. The vector module represents the cardiovascular and respiratory systems performance. Results: Twenty healthy volunteers, twenty people with COPD and five subjects suffering bronchial asthma, during periods without crisis, were studied. The dispersion within the group of each patient was not significant, but a notable difference can be observed between the healthy volunteers and the other people studied. A "normal region" can be set with clearly defined borders. Conclusion: The proposed solution seems promising for evaluating respiratory function even when it is compensated by a cardiac response, making it easier to identify people suffering from respiratory diseases and who may appear normal or healthy.

Auricular vagus nerve stimulator for closed-loop biofeedback-based operation

Auricular vagus nerve stimulation (aVNS) is a novel neuromodulatory therapy used for treatment of various chronic systemic disorders. Currently, aVNS is non-individualized, disregarding the physiological state of the patient and therefore making it difficult to reach optimum therapeutic outcomes. A closed-loop aVNS system is required to avoid over-stimulation and under-stimulation of patients, leading to personalized and thus improved therapy. This can be achieved by continuous monitoring of individual physiological parameters that serve as a basis for the selection of optimal aVNS settings. In this work we developed a novel aVNS hardware for closed-loop application, which utilizes cardiorespiratory sensing using embedded sensors (and/or external sensors), processes and analyzes the acquired data in real-time, and directly governs settings of aVNS. We show in-lab that aVNS stimulation can be arbitrarily synchronized with respiratory and cardiac phases (as derived from respiration belt, electrocardiography and/or photo plethysmography) while mimicking baroreceptor-related afferent input along the vagus nerve projecting into the brain. Our designed system identified > 90% of all respiratory and cardiac cycles and activated stimulation at the target point with a precision of ± 100 ms despite the intrinsic respiratory and heart rate variability reducing the predictability. The developed system offers a solid basis for future clinical research into closed-loop aVNS in favour of personalized therapy.

Evaluation of a novel probe based on laser Doppler flowmetry and comparison with photo plethysmography for assessment of the skin perfusion pressure

This study aims to compare skin perfusion pressure measurements (SPP) at midfoot and below knee level performed with a novel laser Doppler flowmetry (LD) probe with a reference method based on photo plethysmography (PP). It includes 40 patients referred with known or suspected peripheral arterial disease. The SPP was performed with both devices. Blinded re-interpretation of the SPP measurements was carried out by three observers and a consensus quality score was provided for each measurement. SPP >40 mmHg was considered a clinically relevant cut-off. This study evaluates a total of 48 paired measurements of the midfoot and 54 below knee. The two methods agreed in overall diagnostic classification in 80 of 102 measurements (78%) with both methods showing SPP ≥40 mmHg in 21 cases, and both methods showing SPP <40 mmHg in 59 cases. Of the 22 participants with disagreement (22%) in overall classification, 15 had measurements within the range of 30-50 mmHg, and 7 with a clinically relevant disagreement with one device showing SPP <30 mmHg and the other ≥40 mmHg. Analysis of inter observer variation for the LD readings showed an intraclass correlation coefficient of 0.880 (95% CI: 0.807 to 0.929, p- value <0.05) at midfoot, and 0.933 (95% CI: 0.894 to 0.959, p-value <0.05) at below knee level. The novel probe based on LD showed good correlation with PP in absolute pressures, sufficient agreement in overall disease classification as well as good to excellent reliability in terms of inter observer variation.

Remote Design of a Smartphone and Wearable Detected Atrial Arrhythmia in Older Adults Case Finding Study: Smart in OAC – AFNET 9

IntroductionScreening for atrial fibrillation and timely initiation of oral anticoagulation, rhythm management, and treatment of concomitant cardiovascular conditions can improve outcomes in high-risk populations. Whether wearables can facilitate screening in older adults is not known.Methods and AnalysesThe multicenter, international, investigator-initiated, single-arm case-finding Smartphone and wearable detected atrial arrhythmia in older adults case finding study (Smart in OAC – AFNET 9) evaluates the diagnostic yield of a validated, cloud-based analysis algorithm detecting atrial arrhythmias via a signal acquired by a smartphone-coupled wristband monitoring system in older adults. Unselected participants aged ≥65 years without known atrial fibrillation and not receiving oral anticoagulation are enrolled in three European countries. Participants undergo continuous pulse monitoring using a wristband with a photo plethysmography (PPG) sensor and a telecare analytic service. Participants with PPG-detected atrial arrhythmias will be offered ECG loop monitoring. The study has a virtual design with digital consent and teleconsultations, whilst including hybrid solutions. Primary outcome is the proportion of older adults with newly detected atrial arrhythmias (NCT04579159).DiscussionSmart in OAC – AFNET 9 will provide information on wearable-based screening for PPG-detected atrial arrhythmias in Europe and provide an estimate of the prevalence of atrial arrhythmias in an unselected population of older adults.

Body Motion Detection in Neonates Based on Motion Artifacts in Physiological Signals from a Clinical Patient Monitor.

Motion patterns in newborns contain important information. Motion patterns change upon maturation and changes in the nature of motion may precede critical clinical events such as the onset of sepsis, seizures and apneas. However, in clinical practice, motion monitoring is still limited to observations by caregivers. In this study, we investigated a practical yet reliable method for motion detection using routinely used physiological signals in the patient monitor. Our method calculated motion measures with a continuous wavelet transform (CWT) and a signal instability index (SII) to detect gross-motor motion in 15 newborns using 40 hours of physiological data with annotated videos. We compared the performance of these measures on three signal modalities (electrocardiogram ECG, chest impedance, and photo plethysmography). In addition, we investigated whether their combinations increased performance. The best performance was achieved with the ECG signal with a median (interquartile range, IQR) area under receiver operating curve (AUC) of 0.92(0.87-0.95), but differences were small as both measures had a robust performance on all signal modalities. We then applied the algorithm on combined measures and modalities. The full combination outperformed all single-modal methods with a median (IQR) AUC of 0.95(0.91-0.96) when discriminating gross-motor motion from still. Our study demonstrates the feasibility of gross-motor motion detection method based on only clinically-available vital signs and that best results can be obtained by combining measures and vital signs.