Electrocardiographic Device Research Articles

Performance of Single-Lead Handheld Electrocardiograms for Atrial Fibrillation Screening in Primary Care: The VITAL-AF Trial

BackgroundHandheld single-lead electrocardiographic (1L ECG) devices are increasingly used for atrial fibrillation (AF) screening, but their real-world performance is not well understood. ObjectivesThe purpose of this study was to quantify the diagnostic test characteristics of 1L ECG automated interpretations for prospective AF screening. MethodsWe calculated the diagnostic test characteristics of the AliveCor KardiaMobile 1L ECG (AliveCor, US) algorithm using unblinded cardiologist overread as the gold standard using single 30s tracings administered by medical assistants among individuals aged ≥65 years participating in the VITAL-AF trial (NCT03515057) of population-based AF screening embedded within routine primary care. ResultsA total of 14,230 individuals (mean age 74 ± 7 years, 60% women, 82% White) had 31,376 tracings reviewed by 13 cardiologists. A total of 24,906 (79.6%) tracings had an AliveCor interpretation of normal, 5,046 (16.1%) were unclassified, 797 (2.5%) were possible AF, and 573 (1.8%) were no analysis. Cardiologists read 808 (2.6%) tracings as AF. AliveCor possible AF had a PPV of 51.7% (95% CI: 47.8%-55.6%). AliveCor normal had an NPV of 99.8% (95% CI: 99.7%-99.8%). The AliveCor algorithm had an overall sensitivity of 51.0% (95% CI: 47.1%-54.9%) and a specificity of 98.7% (95% CI: 98.6%-98.9%). AliveCor tracings interpreted as unclassified (PPV 5.9%, 95% CI: 5.1%-6.7%) and no analysis (PPV 6.5%, 95% CI: 4.6%-8.9%) had low predictive values for AF and were increasingly prevalent at older ages (13.7% for age 65-69 years to 28.1% for age ≥85 years, P < 0.01). ConclusionsIn an older primary care population undergoing AF screening with handheld 1L ECGs, automated algorithm interpretations were sufficiently accurate to exclude the presence of AF but not to establish an AF diagnosis.

Mobile electrocardiographic devices and healthcare utilization in post-atrial fibrillation ablation patients.

The use of mobile electrocardiogram (mECG) devices is becoming more prevalent. mECG devices allow instant access to recording arrhythmias and enable automatic rhythm interpretation. Providers can remotely evaluate patients and this may reduce in-person healthcare utilization. We sought to evaluate the utility of mECG devices in reducing healthcare utilization among patients who underwent atrial fibrillation (AF) ablation. We identified a population of patients with paroxysmal or persistent AF presenting for their first AF ablation. Patients were divided into two groups: KardiaMobile (AliveCor, Mountain View, CA) mECG users and non-KardiaMobile users. Healthcare utilization was compared between the two groups for one year post-ablation. 184 patients were studied (76 KardiaMobile users, 108 non-KardiaMobile users). There was no difference in the number of office visits (p=0.59), cardiac-specific emergency department visits (p=0.26), cardiac-specific hospital admissions (p=0.13), ablations or cardioversions completed (p=0.24), telephone encounters (p=0.05), patient electronic health record messages (p=0.40), or cardiac imaging (transthoracic or transesophageal echocardiograms) tests ordered (p=0.36). Exposure to the device was associated with a reduction in ambulatory cardiac monitor use (p=0.04). There was no difference in sinus rhythm maintenance over 12months by Kaplan-Meier survival analysis (log rank test p=0.05) between groups. Mobile technology is available for heart rhythm monitoring and can give instant feedback to the user. mECG use is associated with a significant reduction in ambulatory cardiac monitor use in the post-ablation period. There was no difference in other AF-related healthcare utilization.

Validation of Wearable Digital Devices for Heart Rate Measurement During Exercise Test in Patients With Coronary Artery Disease.

To assess the accuracy of recently commercialized wearable devices in heart rate (HR) measurement during cardiopulmonary exercise test (CPX) under gradual increase in exercise intensity, while wearable devices with HR monitors are reported to be less accurate in different exercise intensities. CPX was performed for patients with coronary artery disease (CAD). Twelve lead electrocardiograph (ECG) was the gold standard and Apple watch 7 (AW7), Galaxy watch 4 (GW4) and Bio Patch Mobicare 200 (MC200) were applied for comparison. Paired absolute difference (PAD), mean absolute percentage error (MAPE) and intraclass correlation coefficient (ICC) were evaluated for each device. Forty-four participants with CAD were included. All the devices showed MAPE under 2% and ICC above 0.9 in rest, exercise and recovery phases (MC200=0.999, GW4=0.997, AW7=0.998). When comparing exercise and recovery phase, PAD of MC200 and AW7 in recovery phase were significantly bigger than PAD of exercise phase (p<0.05). Although not significant, PAD of GW4 tended to be bigger in recovery phase, too. Also, when stratified by HR 20, ICC of all the devices were highest under HR of 100, and ICC decreased as HR increased. However, except for ICC of GW4 at HR above 160 (=0.867), all ICCs exceeded 0.9 indicating excellent accuracy. The HR measurement of the devices validated in this study shows a high concordance with the ECG device, so CAD patients may benefit from the devices during high-intensity exercise under conditions where HR is measured reliably.

Evaluation of electrocardiographic parameters in amputee football players.

The present study aimed to compare electrocardiographic (ECG) parameters of amputee football players (AF) with football players without disability (FP) and sedentary individuals without disability (SI). A total of 32 participants (AF = 9, FP = 11, SI = 12) were included in the study. ECG parameters including P-wave amplitude, P-wave duration, PR interval, QRS duration, RR interval, QT interval, corrected-QT interval (QTc), ST segment duration, Tp-e duration, Tp-e/QT and Tp-e/QTc ratios were assessed in all the study participants by using a 12-lead ECG device. OneWay ANOVA Test was used for statistical analysis. Of all ECG parameters, P-wave amplitude and QTc were significantly higher in the AF group in comparison to FP and SI groups. QRS duration was found to be lower in the AF group when compared to FP and SI groups. Myocardial repolarization parameters including Tp-e duration, Tp-e/QT and Tp-e/QTc ratios were similar between groups, as were other parameters such as P-wave duration, PR interval, RR interval, QRS duration and QT interval. It was found that some ECG parameters of amputee football players differ from those with non-disabled players and non-disabled sedentary individuals. These different parameters were within normal limits.

Application of the Alivecor KardiaMobile smartphone modulated ECG device for use in horses.

Electrocardiography is the method used to monitor the electrical impulses in the heart. These diagnostics are increasingly making use of smartphone-based technologies. The objective of this research was to determine whether the Alivecor KardiaMobile (ECGAKM) smartphone-modulated electrocardiographic device, a novel ECG device, can be used to obtain reliable electrocardiogram (ECG) readings in horses. The device was initially tested in 36 Nooitgedacht pony mares to determine the best site of application, method of skin preparation, and ECGAKM device orientation for reliable ECG tracings. Once the most reliable site for ECG acquisition was determined, the device was then applied, in this manner, to 31 Nooitgedacht pony mares and compared with a standard telemetric ECG system (ECGTV). The ECGAKM device was best applied in the fourth intercostal space on the left hemithorax in a vertical orientation and with the skin dampened with 70% ethanol. Mean values determined for RR and QT intervals between the ECGAKMS and ECGTV were not significantly different, however, mean values for the duration of the QRS complexes were significantly different for the two devices. There is acceptable agreement between the ECGTV and ECGAKM devices with regards to the measurement of the PQ; RR and QT intervals but not the QRS duration. The automatically calculated heart rate is not an accurate measure of true heart rate. The Alivecor KardiaMobile (ECGAKM) device can be considered as a simplified screening ECG device in situations where the more standardised system is either unavailable or impractical, but has some limitations.

Automated detection of focal seizures using subcutaneously implanted electrocardiographic device: A proof-of-concept study.

Phase 2 studies showed that focal seizures could be detected by algorithms using heart rate variability (HRV) in patients with marked autonomic ictal changes. However, wearable surface electrocardiographic (ECG) devices use electrode patches that need to be changed often and may cause skin irritation. We report the first study of automated seizure detection using a subcutaneously implantable cardiac monitor (ICM; Confirm Rx, Abbott). For this proof-of-concept (phase 1) study, we recruited six patients admitted to long-term video-electroencephalographic monitoring. Fifteen-minute epochs of ECG signals were saved for each seizure and for control (nonseizure) epochs in the epilepsy monitoring unit (EMU) and in the patients' home environment (1-8 months). We analyzed the ICM signals offline, using a previously developed HRV algorithm. Thirteen seizures were recorded in the EMU, and 41 seizures were recorded in the home-monitoring period. The algorithm accurately identified 50 of 54 focal seizures (sensitivity = 92.6%, 95% confidence interval [CI] = 85.6%-99.6%). Twelve of the 13 seizures in the EMU were detected (sensitivity = 92.3%, 95% CI = 77.2%-100%), and 38 of the 41 seizures in the out-of-hospital setting were detected (sensitivity = 92.7%, 95% CI = 84.7%-100%). Four false detections were found in the 141 control (nonseizure) epochs (false alarm rate = 2.7/24 h). Our results suggest that automated seizure detection using a long-term, subcutaneous ICM device is feasible and accurate in patients with focal seizures and autonomic ictal changes.

Factors affecting wearable ECG device adoption by general practitioners for atrial fibrillation screening: cross-sectional study.

Atrial fibrillation (AF) is a challenging cardiovascular disease worldwide. Wearable electrocardiograph devices (WEDs) have great potential to improve the detection rate of AF in primary care. However, the factors that influence general practitioners' (GPs) perception and acceptance of WEDs are not well understood. To identify factors that influence the intention of GPs to utilize WEDs in a clinical setting to screen patients for AF. The research hypotheses and questionnaire items were designed and developed based on the unified theory of acceptance and technology (UTAUT) framework. We used stratified sampling and obtained the data through an online survey. Structural equation modeling was used to analyze the collected data.Results: A total of 1,004 valid questionnaires from GPs across Sichuan province in China were collected. Three factors increased GPs' intention to utilize WEDs to screen patients for AF, including performance expectancy (β = 0.121, p = 0.004), social influence (β = 0.356, p < 0.001), and price perception (β = 0.587, p < 0.001). Perception risk (β = -0.059, p < 0.001) decreased usage intention, while effort expectancy (β = -0.079, p = 0.155) and facilitating conditions (β = -0.014, p = 0.868) did not affect usage intention. Gender (β = -0.022, p = 0.179), age (β = 0.006, p = 0.699), education level (β = -0.22, p = 0.184) and training (β = 0.007, p = 0.69) were not significantly correlated with usage intention, and these four factors had no moderating effect on the path coefficients. GPs' intention to utilize WEDs is affected by performance expectancy, price perception, perception risk and social influence. Researcher should improve the usability and perception of WEDs for screening and carry out studies to provide high-quality evidence for the security and efficacy of wearable devices.

36 Validation of a smart textile device for heart rate variability in horses at rest

Electrocardiography (ECG) and associated heart rate variability (HRV) are important in the assessment of equine cardiac health, welfare, and performance. Smart textiles have gained popularity as a method to replace standard adhesive electrodes, though limited validation work has been conducted, particularly in veterinary species. Therefore, the objective of this study was to assess the validity of a smart textile ECG device for heart rate (HR) and HRV assessment in horses at rest. Seven mixed-breed, healthy competition horses were recruited for a controlled clinical trial. Horses wore a smart textile ECG device (Skiin Equine) and a standard telemetric device (Televet 100) equipped with adhesive electrodes for simultaneous ECG recordings while unrestrained in stalls for 15 min. Raw data from both devices were analyzed using Kubios Premium to calculate HR and HRV metrics [average and standard deviationof RR intervals, the axial and perpendicular dispersions from the line of identity from the Poincaré plot (SD1 and SD2, respectively), root mean square of successive differences (RMSSD), percentage of successive RR interval differences (pNN50), and oscillations in the very-low frequency (VLF), low-frequency (LF), and high-frequency (HF) bands]. Data were compared using a Bland-Altman analysis with Pearson coefficients. Excellent agreement with small biases were observed between the 2 devices and perfect correlations (r = 1.0, P < 0.0001 for all) were found for all metrics assessed. This study demonstrates that a novel smart textile device can be used interchangeably with the standard telemetric system for assessment of HR and HRV in resting horses.

Usefulness of wearable electrocardiography devices in patients experiencing paroxysmal cardiac-related symptoms: A case series of the “CardioSecur” system

BackgroundElectrocardiograms (ECGs) recorded with wearable devices and additional smartphone apps play an increasing role in cardiology. Case summariesWe present two cases in which it was possible to record an ECG during cardiac-related symptoms using the patients' smartphones. Previous standard resting and 24-hour ECGs had revealed no pathologies. In one case, AV nodal reentry tachycardia was detected and treated accordingly. In the second case, ischemic ECG changes were recorded in a young woman without cardiovascular risk factors during a chest pain episode. Suspecting a coronary vasomotion disorder, an invasive diagnostic procedure was performed. The acetylcholine spasm provocation test revealed coronary microvascular spasm and appropriate therapy was initiated. DiscussionSmartphone-based ECG systems which can be used by the patient independently while experiencing cardiac-related symptoms are a modern diagnostic tool. Considering the use of these systems is beneficial for early diagnosis and appropriate treatment for paroxysmal arrhythmias and coronary vasomotion disorders.

Environmentally Adaptable Organo-Ionic Gel-Based Electrodes for Real-Time On-Skin Electrocardiography Monitoring.

On-skin personal electrocardiography (ECG) devices, which can monitor real-time cardiac autonomic changes, have been widely applied to predict cardiac diseases and save lives. However, current interface electrodes fail to be unconditionally and universally applicable, often losing their efficiency and functionality under harsh atmospheric conditions (e.g., underwater, abnormal temperature, and humidity). Herein, an environmentally adaptable organo-ionic gel-based electrode (OIGE) is developed with a facile one-pot synthesis of highly conductive choline-based ionic liquid ([DMAEA-Q] [TFSI], I.L.) and monomers (2,2,2-trifluoroethyl acrylate (TFEA) and N-hydroxyethyl acrylamide (HEAA). In virtue of inherent conductivity, self-responsive hydrophobic barriers, dual-solvent effect, and multiple interfacial interactions, this OIGE features distinct sweat and water-resistance, anti-freezing and anti-dehydration properties with strong adhesiveness and electrical stability under all kinds of circumstances. In contrast to the dysfunction of commercial gel electrodes (CGEs), this OIGE with stronger adhesion as well as skin tolerability can realize a real-time and accurate collection of ECG signals under multiple extreme conditions, including aquatic environments (sweat and underwater), cryogenic (<-20°C) and arid (dehydration) environments. Therefore, the OIGE shows great prospects in diagnosing cardiovascular diseases and paves new horizons for multi-harsh environmental personalizedhealthcare.

12-lead ECG signal processing and atrial fibrillation prediction in clinical practice.

Because clinically used 12-lead electrocardiography (ECG) devices have high falsepositive errors in automatic interpretations of atrial fibrillation (AF), they require substantial improvements before use. A clinical 12-lead ECG pre-processing method with a parallel convolutional neural network (CNN) model for 12-lead ECG automatic AF recognition is introduced. Raw AF diagnosis data from a 12-lead ECG device were collected and analyzed by two cardiologists to differentiate between true- and false-positives. Using a stationary wavelet transform (SWT) and independent component analysis (ICA) noise reduction was conducted and baseline wandering was corrected for the raw signals. AF patterns were learned and predicted using a parallel CNN deep learning (DL) model. (1) The proposed method alleviates the decreased ECG QRS amplitude enhances the signal-to-noise ratio and clearly shows atrial and ventricular activities. (2) After training, the CNNbased AF detector significantly reduced false-positive errors. The precision of AF diagnosis increased from 77.3% to 94.0 ± 1.5% as compared to ECG device interpretation. For AF screening, the model showed an average sensitivity of 96.8 ± 2.2%, specificity of 79.0 ± 5.8%, precision of 94.0 ± 1.5%, F1-measure of 95.2 ± 1.0%, and overall accuracy of 92.7 ± 1.5%. The method can bridge the gap between the research and clinical practice The ECG signal pre-processing and DL-based AF interpretation can be rapidly implemented clinically.

Age-related reference intervals for ambulatory electrocardiographic parameters in healthy individuals.

The advent of novel monitoring technologies has dramatically increased the use of ambulatory electrocardiography (AECG) devices. However, few studies have conducted detailed large-scale investigations on the incidence of arrhythmias over 24 h, especially ectopy, in healthy individuals over a wide age range. This study aimed to investigate the incidence of arrhythmias detected using AECG and associated factors, in healthy individuals, over a wide age range. In this cross-sectional study, we performed AECG on 365 healthy volunteers (median [interquartile range]: 48 [36, 67], 20-89 years, 165 men) under free-running conditions for 24 h. Ultrasonic echocardiography and heart rate variability analysis were performed to explore the factors associated with the incidence of arrhythmias. The 97.5th percentile of single ventricular ectopy (VE) was 149/day, 254/day, and 1,682/day in the 20-39-, 40-59- and 60-89-year age groups, respectively; that of single supraventricular ectopy (SVE) was 131/day, 232/day, and 1,063/day, respectively. Multivariate analysis revealed that aging was the only independent significant factor influencing the frequency of VE (β = 0.207, P = 0.001). Age (β = 0.642, P < 0.001), body mass index (BMI) (β = -0.112, P = 0.009), and the root mean square of successive differences in RR intervals (β = 0.097, P = 0.035) were factors significantly associated with SVE frequency. Age-specific reference intervals of VE and SVE in a large population of healthy participants over a wide age range were generated. VE and SVE increased with age; SVE was influenced by BMI and the aging-induced decrease in parasympathetic tone activity.

Biodegradable Cellulose Nanocomposite Substrate for Recyclable Flexible Printed Electronics

AbstractPrinted, flexible, and hybrid electronic technologies are advancing rapidly leading to remarkable developments in smart wearables, intelligent textiles, and health monitoring systems. Flexible electronics are typically fabricated on petroleum‐derived polymeric substrates. However, in the light of global environmental concerns regarding fossil raw materials, there is a need to drive the production of flexible electronics devices based on sustainable materials. Additionally, there is a need to reduce the quantity of electronic waste by developing material recovery and recycling technologies. Here, a fully biobased and biodegradable substrate tailored for printed flexible electronic applications is developed. Based on a nanocomposite of cellulose nanofibril (CNF) and hydroxyethyl cellulose (HEC), the substrate shows excellent mechanical and optical properties for printed flexible electronics applications. High‐resolution screen printing of conductive ink and typical electronics assembly processes are possible to realize on the substrate. An electrocardiograph (ECG) device is fabricated on the cellulosic substrate as a technology demonstrator and its performance is confirmed on human volunteers. Last, end‐of‐life scenarios are studied for printed electronic devices where device degradation and subsequent material recovery concepts are presented. This work demonstrates that sustainable plant‐derived materials can play a big role toward a green transition in the electronics industry.

A novel method for conformity assessment testing of electrocardiographs for post-market surveillance purposes.

Monitoring cardiac parameters is the fundamental aspect of every diagnostic process and is facilitated by electrocardiography (ECG) devices. This way, continuous state-of-the-art performance of ECG devices can be ensured. The new Medical Device Regulation (MDR) defines medical device post-market surveillance (PMS) as performed by independent, third-party, notified bodies more strategically in hope to improve traceability of device performance. However, there is still an apparent gap in terms of standardised conformity assessment testing methods. This paper proposes a novel method for conformity assessment testing of ECG devices for post-market surveillance purposes. The method was developed on the basis of International Organisation of Legal Metrology (OIML) guidelines and applied in healthcare institutions from 2018 to 2021. The developed method was validated in healthcare institutions of all levels. The results obtained during validation suggest that conformity assessment testing of the ECG device as a method used during PMS contributes to significant improvement in devices' accuracy and reliability. A standardized approach in conformity assessment testing of ECG devices during PMS, besides increasing reliability of the devices, is the first step in the digital transformation of the management of these devices in healthcare institutions opening possibility for use of artificial intelligence.

Designing Very Fast and Accurate Convolutional Neural Networks With Application in ICD and Smart Electrocardiograph Devices

An implantable cardioverter-defibrillator (ICD) is a device that must detect VT and VF arrhythmias on time and treat them. In this project, three CNN networks are designed to introduce the practical methods of using deep learning in heart electrophysiology signals processing. This project presents two speedy intelligent detection methods of ventricular fibrillation and ventricular tachycardia arrhythmias for ICD devices. It also provides another quick, innovative diagnosis method for use in intelligent electrocardiograph devices to detect abnormal cardiac signals. The first network is 1D-CNN for smart electrocardiographic devices to detect abnormal ECG signals. Dataset MIT-BIH has been used to train this network. This network with the most optimal number of parameters due to high detection speed has a high accuracy of 91%. The second and third networks are 2D-CNNs for use in implantable defibrillators. For the second network, a data set of 20 patients with cardiac arrhythmia and 20 patients without cardiac arrhythmia in an 8-month period of ICD check-up has been prepared. The third network is trained using the Spontaneous Ventricular Tachyarrhythmia Database. The second and third networks are designed to detect EGM signals in VF and VT modes with the optimal number of parameters and 100% accuracy in the second network and 90% in the third network. All three designed networks are in an optimal condition regarding the number of parameters and layers, so they have optimal speed and energy consumption.

Practical R-R Interval Editing for Heart Rate Variability Analysis Using Single-Channel Wearable ECG Devices

Recent innovations in wearable devices have expanded the usage opportunities of single-channel electrocardiography (ECG) recordings in a daily life environment and enabled a variety of indirect daily activity monitoring based on heart rate variability (HRV). In general, wearable ECGs rarely undergo visual inspection by medical experts and therefore may contain noise or artifacts. Although noise/artifact-induced changes in ECG waveforms are known to cause misdetection of the QRS complex (i.e., the most distinguishable ECG components comprised of Q wave, R wave, and S wave), its complete suppression might be technically impossible. Since misdetection occurs in the QRS complex unit, we propose reframing the traditional HRV analysis flow by subdividing the R-R interval (RRI) editing into four steps in accordance with the processing detail (i.e., identification and editing) and its target unit (i.e., QRS complex or RRI). In addition, as a dubious QRS complex identification method for practical use, we utilize the amplitude at the detected point assuming the use of a single-channel wearable ECG without a reference. Initial evaluations using pseudo/real ECG datasets including ECGs with noise and artifacts show that the proposed processing/unit-based subdivision is theoretically effective for improving HRV calculation accuracy, and that the dubious QRS complex identification method for practical use also maintains this effect. Our study starting from practical HRV analysis using single-channel wearable ECG devices encourages reexamining each step in HRV analysis through the interdisciplinary research of clinical medicine and engineering/informatics that reveals the relationship of every two adjacent steps from the perspective of theory and practice.

User-centered design of feedback regarding health-related behaviors derived from wearables: An approach targeting older adults and persons living with neurodegenerative disease.

There has been tremendous growth in wearable technologies for health monitoring but limited efforts to optimize methods for sharing wearables-derived information with older adults and clinical cohorts. This study aimed to co-develop, design and evaluate a personalized approach for information-sharing regarding daily health-related behaviors captured with wearables. A participatory research approach was adopted with: (a) iterative stakeholder, and evidence-led development of feedback reporting; and (b) evaluation in a sample of older adults (n = 15) and persons living with neurodegenerative disease (NDD) (n = 25). Stakeholders included persons with lived experience, healthcare providers, health charity representatives and individuals involved in aging/NDD research. Feedback report information was custom-derived from two limb-mounted inertial measurement units and a mobile electrocardiography device worn by participants for 7-10 days. Mixed methods were used to evaluate reporting 2 weeks following delivery. Data were summarized using descriptive statistics for the group and stratified by cohort and cognitive status. Participants (n = 40) were 60% female (median 72 (60-87) years). A total of 82.5% found the report easy to read or understand, 80% reported the right amount of information was shared, 90% found the information helpful, 92% shared the information with a family member or friend and 57.5% made a behavior change. Differences emerged in sub-group comparisons. A range of participant profiles existed in terms of interest, uptake and utility. The reporting approach was generally well-received with perceived value that translated into enhanced self-awareness and self-management of daily health-related behaviors. Future work should examine potential for scale, and the capacity for wearables-derived feedback to influence longer-term behavior change.

Pilot experience using a portable electrocardiography device for atrial fibrillation detection in an outpatient stroke clinic.

Pilot experience using a portable electrocardiography device for atrial fibrillation detection in an outpatient stroke clinic.

Feasibility of clinical and electrocardiographic follow-up of prinzmetal angina using the metaverse

Abstract Background The recent pandemic triggered an acceleration in adopting innovative technologies and telemedicine novelties. The metaverse, representing a merge of digital worlds using augmented reality (AR) and virtual reality (VR), promises disruptive transformation in healthcare. The feasibility of combining the metaverse with cardiovascular telemedicine services empowering remote consultation as well as assisting heart disease prevention and diagnosis, has not been investigated yet in cardiology. Purpose We evaluated the feasibility of combined clinical and electrocardiographic follow-up inside the metaverse on top of standard of care for a patient who presented with prinzmetal angina. Methods A digital consultation room combining AR/VR was created in a metaverse platform (GDPR compliant, CE marked class I medical device). Patient and cardiologist were given a personal and secured login account. Interactions and connections were made via virtual avatars. Patient was instructed to ask for a consultation in case of any cardiac related symptom occurred. The patient was equipped with a previously validated portable hospital-grade 12-lead smartphone-based electrocardiograph device which was directly integrated to the metaverse platform. Results A 30 years old obese active smoker patient presented for recurrent episodes of typical cardiac chest pain at rest. ECG showed sinus rhythm, normal atrioventricular and intraventricular conduction and no repolarization abnormalities. Laboratory test were normal, echocardiography showed a normal biventricular function with no focal abnormalities or valvular disease. Coronary angiogram excluded the presence of coronary artery disease, and the most possible diagnostic scenario was prinzmetal angina from coronary artery spasm. The patient was therefore discharged under treatment with diltiazem 120 mg twice daily, a multiple lead smartphone ECG device as well as the access to metaverse via his avatar, since no ECG were available during the episodes. Ten days later, the patient experienced an episode of palpitation accompanied with general discomfort. He subsequently logged into the metaverse where the cardiologist was available. The anamnesis of the episode was collected as well as the auto-recorded ECG by the patient. Although the clinical and electrocardiographic data were reassuring, the physician proposed to seek for medical attention. Hospital work up was consistent with the diagnosis provided in the virtual consultation. Conclusions To our knowledge, we conducted the first medical act in cardiology inside the metaverse combining VR environment with existing cardiovascular technological innovations as support information to the standard of care. Exploiting the full potential of the metaverse could serve as an unparalleled leap in the way cardiovascular medicine is delivered and could introduce new dimensions to cardiology in terms of health education, disease prevention and diagnosis. Funding Acknowledgement Type of funding sources: None.

A Smart Textile Band Achieves High-Quality Electrocardiograms in Unrestrained Horses.

Electrocardiography (ECG) is an essential tool in assessing equine health and fitness. However, standard ECG devices are expensive and rely on the use of adhesive electrodes, which may become detached and are associated with reduced ECG quality over time. Smart textile electrodes composed of stainless-steel fibers have previously been shown to be a suitable alternative in horses at rest and during exercise. The objective of this study was to compare ECG quality using a smart textile girth band knit with silver and carbon yarns to standard adhesive silver/silver chloride (Ag/AgCl) electrodes. Simultaneous three-lead ECGs were recorded using a smart textile band and Ag/AgCl electrodes in 22 healthy, mixed-breed horses that were unrestrained in stalls. ECGs were compared using the following quality metrics: Kurtosis (k) value, Kurtosis signal quality index (kSQI), percentage of motion artifacts (%MA), peak signal amplitude, and heart rate (HR). Two-way ANOVA with Tukey's multiple comparison tests was conducted to compare each metric. No significant differences were found in any of the assessed metrics between the smart textile band and Ag/AgCl electrodes, with the exception of peak amplitude. Kurtosis and kSQI values were excellent for both methods (textile mean k = 21.8 ± 6.1, median kSQI = 0.98 [0.92-1.0]; Ag/AgCl k = 21.2 ± 7.6, kSQI = 0.99 [0.97-1.0]) with &lt;0.5% (&lt;1 min) of the recording being corrupted by MAs for both. This study demonstrates that smart textiles are a practical and reliable alternative to the standard electrodes typically used in ECG monitoring of horses.