Electrocardiographic Measurements Research Articles

Association of leukocyte telomere length with cardiac conduction disease and sick sinus syndrome

Abstract Background Cardiac conduction disease (CCD) and sick sinus syndrome (SSS) may be related to a degenerative process. Leukocyte telomere length (LTL) is associated with the aging process and age-related degenerative diseases. We aimed to investigate the association between LTL and the risks of CCD/SS, and to explore whether LTL is related with cardiovascular imaging and electrocardiographic (ECG) changes. Methods This is a population-based cross-sectional study of UK Biobank participants without history of CCD/SSS recruited from 2006 to 2010. LTL was measured using a quantitative polymerase chain reaction method. Cardiovascular measurements were derived from cardiovascular magnetic resonance using machine learning. The median (IQR) duration of follow-up was 12.0 (11.3-12.7) years. The associations of LTL with imaging and ECG measurements and incident CCD/SSS were evaluated by multivariable regression models. Results Among the 412,452 white participants, 188,891 (45.8%) were male, with a mean age of 57.3 years. Longer LTL was independently associated with positive cardiac remodeling, including higher left ventricular mass, larger atrial volume, and increased atrial stroke volumes. However, no significant associations were observed with ECG findings including PR interval and P-wave duration. 11991 (2.6%) participants developed CCD and 984 (0.2%) developed SSS. Longer LTL was not associated with younger age. However, longer LTL was not associated with a lower risk of incident CCD (LTL fourth quartile vs. first quartile: hazard ratio, 0.98; 95% CI, 0.97-1.0; P = 0.057) or SSS (LTL fourth quartile vs. first quartile: hazard ratio, 0.98; 95% CI, 0.92-1.05; P = 0.554). Conclusions In this cross-sectional study, longer LTL was associated with a larger atrial size with better atrial function in middle age, but not with ECG changes. However, longer LTL was not associated with a lower risk of incident CCD and SSS.

Speckle Plethysmograph-Based Blood Pressure Assessment

Continuous non-invasive blood pressure (CNBP) monitoring is of the utmost importance in detecting and managing hypertension, a leading cause of death in the United States. Extensive research has delved into pioneering methods for predicting systolic and diastolic blood pressure values by leveraging pulse arrival time (PAT), the time difference between the proximal and distal signal peaks. The most widely employed pairing involves electrocardiography (ECG) and photoplethysmography (PPG). Possessing similar characteristics in terms of measuring blood flow changes, a recently investigated optical signal known as speckleplethysmography (SPG) showed its stability and high signal-to-noise ratio compared with PPG. Thus, SPG is a potential surrogate to pair with ECG for CNBP estimation. The present study aims to unlock the untapped potential of SPG as a signal for non-invasive blood pressure monitoring based on PAT. To ascertain SPG’s capabilities, eight subjects were enrolled in multiple recording sessions. A third-party device was employed for ECG and PPG measurements, while a commercial device served as the reference for arterial blood pressure (ABP). SPG measurements were obtained using a prototype smartphone-based system. Following the completion of three scenarios—sitting, walking, and running—the subjects’ signals and ABP were recorded to investigate the predictive capacity of systolic blood pressure. The collected data were processed and prepared for machine learning models, including support vector regression and decision tree regression. The models’ effectiveness was evaluated using root-mean-square error and mean absolute percentage error. In most instances, predictions utilizing PATSPG exhibited comparable or superior performance to PATPPG (i.e., SPG Rest ± 12.4 mmHg vs. PPG Rest ± 13.7 mmHg for RSME, and SPG 8% vs. PPG 9% for MAPE). Furthermore, incorporating an additional feature, namely the previous SBP value, resulted in reduced prediction errors for both signals in multiple model configurations (i.e., SPG Rest ± 12.4 mmHg to ±3.7 mmHg for RSME, and SPG Rest 8% to 3% for MAPE). These preliminary tests of SPG underscore the remarkable potential of this novel signal in PAT-based blood pressure predictions. Subsequent studies involving a larger cohort of test subjects and advancements in the SPG acquisition system hold promise for further improving the effectiveness of this newly explored signal in blood pressure monitoring.

Outcome of serial cardiac evaluations during doxorubicin-based chemotherapy in small- to medium-sized dogs with multicentric lymphoma

Doxorubicin is an anthracycline antitumor antibiotic with dose-dependent and cumulative cardiotoxicity. However, the necessity for serial cardiac evaluation is unknown in dogs without risk factors for dilated cardiomyopathy (DCM). This study aimed to investigate serial changes in echocardiographic and electrocardiographic measures in small- and medium-sized dogs after four doxorubicin doses. We included 17 dogs, weighting < 20 kg, with multicentric lymphoma. All dogs received doxorubicin over 30 min every 4 weeks as part of a multi-drug chemotherapy protocol. The average doxorubicin dose was 3.8 times per dog. Clinical cardiotoxicity was not observed during the monitoring period. The incidence of developing arrhythmia was not significantly associated with the number of doxorubicin doses received (P = 0.600). The development of valvular regurgitations and mitral regurgitation in these dogs was not significantly associated with the number of doxorubicin doses (P = 0.363 and P = 0.779, respectively). The other echocardiographic results were not significantly different between each evaluation. In conclusion, our results showed no significant cardiotoxicity under echocardiogram and electrocardiogram in small- and medium-sized dogs without risk factors for DCM after four doses of doxorubicin in a 30-minute infusion method.

Evaluating the Effects of Acute and Chronic Doxorubicin Administration on Cardiac Function Through Electrocardiographic Measurements

Background: The medications used to treat cancer can lead to cardiac problems, which restricts their use. Furthermore, the method these medications are taken seems to have an impact on varied out-comes. Therefore, this study aimed to examine whether administering doxorubicin (DOX) agent acutely and chronically has distinct impacts on the electrical activity of the heart. Materials and Methods: Twenty-six male Wistar-Albino rats, weighing between 200-250 grams, were split into three groups: control group; no treatment was applied to animals (n=8), DOX acute group: a single dosage of 15.05 mg/kg of DOX was given at the end of the 3 weeks (n=8), DOX chronic group; which received an intraperitoneal (i.p.) 2.15 mg/kg DOX for 3 weeks, 7 doses in total (n=10). At the end of the experimental period, electrocardiogram (ECG) measurements were taken for all animals and evaluated. Results: ECG data showed that heart rate (HR), P wave amplitude, and P duration did not differ between the acute and control groups but did statistically significantly declined in the chronic group. In both DOX groups, PR interval remained unchanged compared to the control. Also, RR interval increased significantly in the chronic group while it remained unchanged in the acute DOX dose group. The QRS duration was found to have considerably increased in both DOX groups. Furthermore, it was found that both DOX groups had a considerable increase in the QT interval, although the chronic group's increase was more noticeable. Conclusions: In conclusion, it is thought that the ways in which these medications are administered may result in significant variations in heart function. Acute DOX treatment appears to be less harmful than chronic exposure, as evidenced by its lack of adverse effects, particularly on P wave amplitude (a measure of atrial contraction) and P wave duration (the length of the contraction). However, more research is required to validate these findings. Key Words: Electrocardiogram (ECG), Doxorubicin (DOX), Cardiotoxicity

Cardiogenic Shock Intravascular Cooling Trial (CHILL-SHOCK)

Cardiogenic shock (CS) is complicated by high mortality rates. Targeted temperature control (TTC) has been proposed as an adjunct therapy in CS. This study aims to examine the safety of TTC in patients presenting with CS. In this open-label, randomized controlled pilot trial, 20 patients with hemodynamic criteria for CS were assigned to standard of care plus TTC vs standard of care alone. The primary outcome was a composite safety outcome, including well-described complications of TTC. Secondary outcomes included mortality at 90 days, invasive hemodynamic and echocardiographic parameters, electrocardiographic measurements, and inotrope dosing. There were no significant differences in the composite analysis of prespecified safety outcomes (3 events in the TTC group vs 0 events in the control group; P = 0.24). Patients randomized to TTC demonstrated a statistically significant increase in cardiac index and cardiac power index compared to the control group at 48-96 hours after randomization (3.6 [3.1, 3.9] L/min/m2 vs 2.6 [2.5, 3.15] L/min/m2; P = 0.029 and 0.61 [0.55, 0.7] W/m2 vs 0.53 [0.435, 0.565] W/m2; P = 0.029, respectively). TTC may be a safe adjunct therapy for patients presenting with CS and may yield improvement in specific hemodynamic parameters.

Heart rate detection method based on Ballistocardiogram signal of wearable device：Algorithm development and validation

BackgroundHeart rate, as the four vital signs of human body, is a basic indicator to measure a person's health status. Traditional electrocardiography (ECG) measurement, which is routinely monitored, requires subjects to wear lead electrodes frequently, which undoubtedly places great restrictions on participants' activities during the normal test. At present, the boom of wearable devices has created hope for non-invasive, simple operation and low-cost daily heart rate monitoring, among them, Ballistocardiogram signal (BCG) is an effective heart rate measurement method, but in the actual acquisition process, the robustness of non-invasive vital sign collection is limited. Therefore, it is necessary to develop a method to improve the robustness of heart rate monitoring. ObjectiveTherefore, in view of the problem that the accuracy of untethered monitoring heart rate is not high, we propose a method aimed at detecting the heartbeat cycle based on BCG to accurately obtain the beat-to-beat heart rate in the sleep state. MethodsIn this study, we implement an innovative J-wave detection algorithm based on BCG signals. By collecting BCG signals recorded by 28 healthy subjects in different sleeping positions, after preprocessing, the data feature set is formed according to the clustering of morphological features in the heartbeat interval. Finally, a J-wave recognition model is constructed based on bi-directional long short-term memory (BiLSTM), and then the number of J-waves in the input sequence is counted to realize real-time detection of heartbeat. The performance of the proposed heartbeat detection scheme is cross-verified, and the proposed method is compared with the previous wearable device algorithm. ResultsThe accuracy of J wave recognition in BCG signal is 99.67%, and the deviation rate of heart rate detection is only 0.27%, which has higher accuracy than previous wearable device algorithms. To assess consistency between method results and heart rates obtained by the ECG, seven subjects are compared using Bland-Altman plots, which show no significant difference between BCG and ECG results for heartbeat cycles. ConclusionsCompared with other studies, the proposed method is more accurate in J-wave recognition, which improves the accuracy and generalization ability of BCG-based continuous heartbeat cycle extraction, and provides preliminary support for wearable-based untethered daily monitoring.

Digitized Electrocardiography Measurements Support the Biological Plausibility of the Pathological Significance of ST Segments in Athletes.

ST segment deviations around the isoelectric line are common findings in manifest cardiovascular disease. In athletes, ST elevation is common, while ST depression is considered rare. However, clinical studies in athletes have associated ST depression with myocardial fibrosis and fatty infiltration and ST elevation with pericarditis and myocarditis. This study aims to explore the association between resting ST segment deviations and resting heart rate, an indicator of training and autonomic tone and electrocardiography (ECG) markers of exercise training effect and cardiovascular health R and T wave amplitude. Retrospective analysis of digitized ECG data. Institutional setting. Seven thousand eight hundred thirty-six (male athletes = 4592, female athletes = 3244) healthy asymptomatic athletes (14-35 years). A series of correlations and regressions were conducted between ST depression (<0.0 µV) and ST elevation (>0.0 µV), on R and T wave amplitudes, and heart rate in leads V2, V5, and aVF. Positive correlations between ST elevation and R and T wave (S wave in V2) amplitudes and leads V5, V2, and aVF in male and female athletes (range of r = 0.1-0.54). In addition, there was a negative correlation between ST elevation and HR for male and female athletes. Finally, there was a negative correlation between ST depression and R wave and HR for male and female athletes in V5 ( P < 0.01). In athletes, ST segment elevation is correlated with R and T wave amplitudes and negatively correlated with HR. In addition, ST segment elevation is correlated with low heart rate, consistent with its higher prevalence in athletes. ST segment depression is not influenced by HR but is negatively associated with R and T wave amplitudes.

Predicting Individual Survival Distributions Using ECG: A Deep Learning Approach Utilizing Features Extracted by a Learned Diagnostic Model

In the field of healthcare, individual survival prediction is important for personalized treatment planning. This study presents machine learning algorithms for predicting Individual Survival Distributions (ISD) using electrocardiography (ECG) data in two different formats. The models, which predict time until death, are developed and evaluated on a large, population-based cohort from Alberta, Canada. Our results demonstrate that models trained on raw ECG waveforms significantly outperform those trained on traditional ECG measurements in several metrics, including concordance index, hinge L1 loss, margin L1 loss, and margin truncated L1 loss. Additionally, the integration of predicted probabilities from wide-range diagnostic tasks not only enhances our ISD models' performance but also makes them significantly superior to other models across all evaluation metrics in individual survival prediction tasks. This innovative approach highlights the potential to leverage insights from diagnostic models for prognostic tasks, such as individual survival prediction. These findings could have far-reaching implications for the development of personalized treatment plans and open new avenues for future research in survival prediction using ECGs.

Atrial Fibrillation Detection from Compressed ECG Measurements for Wireless Body Sensor Network

Recent years have witnessed an increasing prevalence of wearable devices in the public, where atrial fibrillation (AF) detection is a popular application in these devices. Generally, AF detection is performed on cloud whereas this paper describes an on-device AF detection method. Technically, compressed sensing (CS) is first used for electrocardiograph (ECG) acquisition. Then QRS detection is proposed to be performed directly on the compressed CS measurements, rather than on the reconstructed signals on the powerful cloud server. Based on the extracted QRS information, AF is determined by quantitatively analyzing the ( RR , dRR ) plot. Databases with ECG samples collected from both medical-level (MIT-BIH afdb) and wearable ECG devices (Physionet Challenge 2017) are introduced for performance validation. The experiment results well demonstrate that our on-device AF detection algorithm can approach the performance of those implemented on the raw signals. Our proposal is suitable for AF screening directly on the wearable devices, without the support of the data center for signal reconstruction and intelligent analysis.

A review of driver cognitive load detection using ECG signals

Detection of the driver’s cognitive load while driving is crucial to prevent the likelihood of traffic collisions and improve road safety. A physiological-based approach has gained significant attention due to its potential to provide reliable indicators for the driver’s state. The physiological signal of electrocardiography (ECG) is considered a promising biomarker for detecting the driver’s cognitive load. Despite the interest in cognitive load detection using ECG, an attempt has yet to be made to identify the relationship between ECG measures and driver cognitive load level. This paper seeks to investigate this gap in cognitive load literature. The finding demonstrates that further research is still needed on ECG-based driver’s cognitive load detection by examining and analyzing the limitations of research challenges and earlier studies. This study also addresses the performance and problems faced in the detection of a driver’s cognitive load considering ECG. With a better understanding of how cognitive load affects ECG measures, both researchers and companies can design more effective driver’s state detection systems.

Incidence and Predictors of Left Ventricular Thrombus Formation After Acute Myocardial Infarction With ST-Segment Elevation.

Background and objective Our prospective study aimed to evaluate the frequency and risk factors of left ventricular thrombus (LVT) occurring after acute ST-segment elevation myocardial infarction (STEMI) in the era of primary percutaneous coronary intervention (PCI). Methods Our study included 131 patients diagnosed with acute STEMI who were followed up and treated. The presence of the thrombus was determined by transthoracic echocardiography (TTE). Study patients were evaluated as cases of thrombus (+) and thrombus (-). The relationship of electrocardiographic measurements such as the number of leads with pathological Q waves, ST segment deviation score, QT dispersion, and echocardiographic measurements such as ejection fraction (EF), end-systolic and end-diastolic volumes, and wall motion score index (WMSI) with LVT was investigated. LVT risk factors were identified. Results The median age of the study patients was 59.7 ± 11.7 years, and 84.7% were male. The incidence of LVT was 17.6% (23 patients). While the anterior STEMI rate was 86.9% in the thrombus (+) group, it was 50.9% in the thrombus (-) group (p<0.001). While WMSI was 2.1 ± 0.44 in the thrombus (+) group, it was calculated as 1.40 ± 0.31 in the thrombus (-) group (p<0.001). In the thrombus (+) group, EF was found to be lower, end-systolic and end-diastolic volumes were higher, and the rate of moderate and severe mitral regurgitation and the rate of aneurysmatic segment detection were higher. LVT had a moderate correlation with WMSI (r: 0.613; p<0.001), the presence of an aneurysmatic segment (r: 0.549; p<0.001), and EF (r: -0.514; p<0.001). Presentation with anterior STEMI (odds ratio [OR]: 4.266; p<0.001), WMSI (OR: 7.971; p=0.012), the number of leads with pathological Q waves detected at discharge (OR: 3.651; p=0.009), the presence of an aneurysmatic segment (OR: 2.089, p=0.009), and EF (OR: 1.129, p=0.006) were identified as independent risk factors of the presence of LVT. The area under the curve for WMSI was found to be 0.910 (95% CI: 0.852-0.968). A WMSI cut-off of 1.56 identified LVT with 91% sensitivity and 70% specificity (Youden index: 0.617). Conclusion In the primary PCI era, LVT incidence after acute STEMI is still significant. Anterior STEMI, the number of leads with pathological Q waves detected at discharge, WMSI, aneurysm formation, and low EF are independent risk factors for LVT. Among these risk factors, the variable with the highest diagnostic power is WMSI.

A Multimodal Late Fusion Framework for Physiological Sensor and Audio-Signal-Based Stress Detection: An Experimental Study and Public Dataset

Stress can be considered a mental/physiological reaction in conditions of high discomfort and challenging situations. The levels of stress can be reflected in both the physiological responses and speech signals of a person. Therefore the study of the fusion of the two modalities is of great interest. For this cause, public datasets are necessary so that the different proposed solutions can be comparable. In this work, a publicly available multimodal dataset for stress detection is introduced, including physiological signals and speech cues data. The physiological signals include electrocardiograph (ECG), respiration (RSP), and inertial measurement unit (IMU) sensors equipped in a smart vest. A data collection protocol was introduced to receive physiological and audio data based on alterations between well-known stressors and relaxation moments. Five subjects participated in the data collection, where both their physiological and audio signals were recorded by utilizing the developed smart vest and audio recording application. In addition, an analysis of the data and a decision-level fusion scheme is proposed. The analysis of physiological signals includes a massive feature extraction along with various fusion and feature selection methods. The audio analysis comprises a state-of-the-art feature extraction fed to a classifier to predict stress levels. Results from the analysis of audio and physiological signals are fused at a decision level for the final stress level detection, utilizing a machine learning algorithm. The whole framework was also tested in a real-life pilot scenario of disaster management, where users were acting as first responders while their stress was monitored in real time.

Precordial electrocardiographic recording and QT measurement from a novel wearable ring device

BackgroundThe availability of portable and wearable electrocardiography devices has increased secondary to technological development. Single-lead ECG recordings have been shown to reliably detect and characterize cardiac rhythms such as atrial fibrillation. Acquisition of precordial electrodes for full 12-lead ECG reconstruction from bipolar recordings is complicated by the absence of a body ground / Wilson central terminal electrode, however the extent of difference between standard precordial lead and those from a wearable bipolar ECG recorder has not been characterized. ObjectiveThis study characterizes precordial ECG lead set from sequential bipolar recordings from an ECG ring wearable device. MethodsIn 70 patients wearing an ECG device on their right finger, sequential precordial leads (CR1-CR6) were obtained along with chest electrodes (V1-V6). During acquisition of the modified precordial lead CR6 a full standardized 12 lead ECG capture was obtained.Using automated analysis software, signal quality was assessed, and the correlation values between the ring-derived ECG precordial leads and standard ECG leads were compared with QRS duration, QT width, and RR interval measurement. ResultsThere is high concordance in the morphology of precordial ECG leads obtained in a standard fashion and those recorded through an ECG ring. Morphologic alignment improved with increasing laterality of the precordial lead with chest to right arm ring recording (CR5, CR6) compared with anterior chest leads to right arm (CR1, CR2). Segmental measurements of QRS duration and QT segment were well aligned and of high correlation. ConclusionWearable ring based electrocardiographic technology is capable of high fidelity recording of precordial leads for non-simultaneous reconstruction of complete ECG sets. These correlate highly with surface-obtained QRS and QT duration measurement, which has significant implications for clinical applications. Uninterpretable tracings were primarily due to electrode noise from poor electrode contact.

Speckle tracking echocardiography for diagnosis of right ventricular failure in children with totally corrected tetralogy of Fallot in Sulaimani, Iraq

ObjectivesThe study was aimed at using speckle tracking echocardiography as a novel technique to diagnose right ventricular failure (RVF) in children with total correction of tetralogy of Fallot (TOF) through surgery. MethodsA quasi-experimental study was performed at the Children's Heart Hospital of Sulaimani for 9 months. A total of 150 children with completely repaired TOF were enrolled to investigate RVF. Conventional echocardiographic data were recorded, including right ventricular (RV) ejection fraction (EF), tricuspid annular plane systolic excursion (TAPSE), myocardial performance index (MPI), and RV end-systolic and diastolic volume (RVESV and RVEDV). Additionally, speckle tracking was performed for the regional and longitudinal strain and strain rate in four-chamber apical view. RVF diagnosis was determined on the basis of electrocardiography measurement of P-wave dispersion, T-wave dispersion, and QRS duration. ResultsChildren with repaired TOF who were diagnosed with RVF through conventional echocardiography exhibited abnormalities with respect to children with normal RV function, including a TAPSE of 1.3 ± 0.11 cm, RVEF of 35.5 ± 6.72, RVESV of 69.8 ± 15.13 ml, RVEDV of 110.1 ± 14.13 ml, MPI of 0.60 ± 0.12, and Pmax of 52.4 ± 14.08. The use of speckle tracking in RVF diagnosis revealed a relatively lower longitudinal strain and strain rate (−12.1 ± 2.3 and −0.9 ± 0.3, respectively) in the children with RVF. Moreover, longitudinal right ventricular strain was positively correlated with TAPSE (r = 0.656) and EF (r = 0.675), and negatively correlated with RVEDV (r = −0.684), RVESV (r = −0.718), MPI (r = −0.735), and Pmax (r = −0.767). ConclusionsThe application of speckle tracking with the longitudinal RV strain and strain rate to estimate RV function in children with repaired TOF is a new advanced method that, compared with conventional echo, significantly improves the diagnosis of regional myocardial deformations and cardiac muscle motion velocity.

Smartphone-based six-lead ECG: A new device for electrocardiographic recording in dogs

Smartphone-based technology for electrocardiographic recording is now part of the new concept of mobile health in both human and veterinary medicine. Although smartphone-based ECG for electrocardiographic screening in dogs is reliable, one-lead ECG devices have mainly been evaluated. This prospective study assessed the feasibility and the diagnostic reliability of a new smartphone-based six-lead electrocardiograph (smECG) in dogs, in comparison to a standard six-lead electrocardiograph (stECG). All ECG tracings were blindly reviewed by an expert operator, who judged whether tracings were acceptable for interpretation, performed the electrocardiographic measurements, and assigned a diagnosis. The agreement in the electrocardiographic interpretation and diagnosis between smECG and stECG was assessed using the Bland-Altman test and Cohen's k test.The study included 108 client-owned dogs. The tracings obtained by the smECG were interpretable in 100 % of cases. No clinically relevant differences between smECG and stECG were found in the assessment of heart rate, interval duration, and QRS mean electrical axis. The smECG tended to underestimate the amplitude of the P and R waves. Perfect agreement was found in the detection of sinus rhythm, atrial fibrillation, ventricular arrhythmias, atrioventricular blocks, and bundle branch blocks. Our study suggests that the tested smartphone-based six-lead ECG is a clinically reliable device for the assessment of heart rate and heart rhythm in dogs, and thus could be used in a clinical setting in dogs and for telemedicine.

Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities.

The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications.

Abstract 16984: A Wearable Device Reproducibly Identifies Premature Ventricular Contractions and Tachyarrhythmias in Heart Failure Patients

Introduction: occurrence of ventricular arrhythmias (VAs) has a dramatic impact on prognosis of patients with heart failure (HF). Hypothesis: wearable devices, including smartwatch (SW), might provide real-time informations in patients at risk of VAs. Aims: we therefore evaluated if SW detection of QRS interval width and voltage could reproducibly detect VAs and/or premature ventricular contractions (PVCs) in HF patients. Methods: HF patients (N=100) underwent continuous electrocardiographic (ECG) recordings through telemetry and SW during hospital admission. Left ventricular ejection fraction (EF) and laboratory pro-BNP levels assessments were obtained as well. Correlation of the ECG results was addressed using Pearson’s analysis for normally distributed data and Spearman’s analysis for non-parametric data. Bland-Altman was used for reliability between telemetry and SW ECG measurements. Results: mean EF was 45.92±12.12%; mean pro-BNP was 2826±5823 pg/mL. Using the SW and the ECG data, QRS width and voltage correlation coefficients were 0.990 (p&lt;0.001) and 0.974 (p&lt;0.001), respectively. Concordance was found between the two assessments for QRS width (bias, 0.20; SD 3.0; lower limit, –5.68; upper limit, 6.08), and voltage (bias, -0.029; SD, 0.611; lower limit, –1.227; upper limit, 1.169). Moreover, we found correlation coefficients of 0.964 (p&lt;0.001) and 0.970 (p&lt;0.001), respectively, for PVCs width and PVCs voltage using SW and telemetry or other ECG report. Similarly, both techniques showed positive concordance for PVCs width (bias, 0.368; SD, 2.65; lower limit, -4.83; upper limit, 5.56) and PVCs voltage (bias, 0.54; SD, 1.25; lower limit, -1.91; and upper limit, 2.996). Remarkably, VAs identification by the SW was reproducible and standardized. Conclusions: continuous monitoring through SW might be considered in HF patients upon discharge.

Effects of Cognitive Demand Levels for Various Horticultural Activities on Psychophysiological Responses in Adults

We compared the effects of horticultural activities according to cognitive demand levels on psychophysiological responses in adults. Thirty-two adults in their 20s were included. Participants performed 10 horticultural activities (raking, planting transplants, fertilizing, tying plants to stakes, harvesting, sowing, conducting cuttage, planting potted plants, cutting and washing, arranging flowers) for 150 seconds at two levels of cognitive demand. Electroencephalographic (EEG) and electrocardiographic measurements were acquired during the activity. After each activity, the participants’ emotional states were evaluated using the semantic differential method (SDM). The EEG results, according to comparison by activity, showed that for nine activities, excluding raking, relative theta decreased when performing tasks at a level of high cognitive difficulty (HCD) compared with those with a low cognitive difficulty (LCD), and relative beta, relative gamma, fast alpha, and relative low beta increased, indicating activation of the prefrontal cortex. In the relative theta power spectra, the cuttage activity was found to be the lowest when performing tasks at a high level high cognitive difficulty, and the working memory function was activated the most compared with other activities. When sowing at a low level of cognitive demand, participants’ heart rate decreased and stabilized. When potted plants were harvested at a high level of cognitive difficulty, the ratio of low frequency to high frequency increased, and the sympathetic nervous system was activated. In addition, when planting transplants, and cutting and washing were performed at a high level of cognitive difficulty, and the standard deviation of the RR interval was high, indicating a high ability of the autonomic nervous system to resist stress. As a result of the SDM, the emotional state according to task difficulty was found to be more stable and relaxed than high cognitive difficulty, but a significant increase in comfort, relaxation, and naturalness was achieved when nine gardening tasks with low cognitive difficulty were performed, with the exception of sowing. The results of this study show that tasks with high cognitive difficulty activate working memory, whereas those with low cognitive difficulty stabilize and relax brain activation. Therefore, this study confirmed that an intervention in horticultural activities with an appropriate level of cognitive difficulty could have a significant effect on psychophysiological changes in adults.

Protective effect of MitoTEMPO against cardiac dysfunction caused by ischemia–reperfusion: MCAO stroke model study

Purpose Neurological impairments are the leading cause of post-stroke mortality, while stroke-related cardiovascular diseases rank second in significance. This study investigates the potential protective effects of MitoTEMPO (2,2,6,6-tetramethyl-4-[[2-(triphenylphosphonio) acetyl] amino]-1-piperidinyloxy, monochloride, monohydrate), a mitochondria-specific antioxidant, against cardiac and neurological complications following stroke. The objective is to assess whether MitoTEMPO can be utilized as a protective agent for individuals with a high risk of stroke. Materials and methods Seventeen-week-old male Wistar Albino rats were randomly assigned to three groups: SHAM, ischemia–reperfusion and MitoTEMPO + ischemia–reperfusion (MitoTEMPO injection 0.7 mg/kg/day for 14 days). The SHAM group underwent a sham operation, while the ischemia–reperfusion group underwent 1-h middle cerebral artery occlusion followed by three days of reperfusion. Afterwards, noninvasive thoracic electrical bioimpedance and electrocardiography measurements were taken, and sample collection was performed for histological and biochemical examinations. Results Our thoracic electrical bioimpedance and electrocardiography findings demonstrated that MitoTEMPO exhibited a protective effect on most parameters affected by ischemia–reperfusion compared to the SHAM group. Furthermore, our biochemical and histological data revealed a significant protective effect of MitoTEMPO against oxidative damage. Conclusions The findings suggest that both ischemia–reperfusion-induced cardiovascular abnormalities and the protective effect of MitoTEMPO may involve G-protein coupled receptor-mediated signaling mechanisms. This study was conducted with limitations including a single gender, a uniform age group, a specific stroke model limited to middle cerebral artery, and pre-scheduled only one ischemia–reperfusion period. In future studies, addressing these limitations may enable the implementation of preventive measures for individuals at high risk of stroke.

Biocompatible Gel-Free Coconut Oil and Carbon Black Electrodes for ECG and Respiration Measurements

The current state of the art in telemedicine has increased the interest in long term monitoring of physiological and bioelectric signals. This motivated the development of materials and techniques for the fabrication of biocompatible, user and environmentally friendly alternatives to conventional resistive wet electrodes. Here we report a method for the fabrication of dry flexible and stretchable electrodes based on Coconut-Oil and Carbon Black for the monitoring of electrophysiological signals without conductive gels. The highly stretchable material shows a specific resistance ρ down to 33.2±12.3Ωm, high conformability, and a stretchability up to 1500%. The epidermal electrodes were used to record Electrocardiographic (ECG) signals and measure respiration in a 3-lead configuration and compared to commercial wet electrodes. Even after being elongated by 100% for 100 stretch/release cycles, a reliable recording of the QRS-complex is demonstrated without the need for any contact enhancer or substances that cause skin reaction, demonstrating the potential use of this material for long term ECG monitoring applications.