Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives

Portable ECG and PCG wireless acquisition system and multiscale CNN feature fusion Bi-LSTM network for coronary artery disease diagnosis

Coronary artery disease (CAD) is a major cause of mortality, especially among aging populations, making timely and accurate diagnosis essential. In this work, a portable wireless device powered by artificial intelligence for CAD detection is proposed, which synchronously captures electrocardiograms (ECG) and phonocardiograms (PCG) signals and transmits them for real-time analysis and visualization. To ensure the reliability of the acquired signals, a Hidden Semi Markov model is applied to validate data quality. Then, a multiscale convolutional neural network (CNN) feature fusion model extracts critical features from the PCG and ECG signals. All these features and signal information are later processed by a bidirectional long short-term memory (Bi-LSTM) network. Our network achieves impressive metrics and maintains reliable performance in practical tests. This straightforward diagnostic system offers a practical and technically feasible solution for the effective diagnosis of CAD, leveraging advanced neural network architectures for robust clinical application.

Home detection of atrial fibrillation using cardiac activity analysis: technologies available to the patient

INTRODUCTION

Atrial fibrillation (AF) is the most common cardiac arrhythmia, whose incidence and prevalence have increased over the last 20 years and will continue to increase over the next 30 years. It is characterized by irregular atrial activation, leading to complications as stroke and heart failure. Due to its intermittent and asymptomatic nature, diagnosing and monitoring AF is challenging but crucial for effective treatment and prevention of serious complications.

AREAS COVERED

This study reviews noninvasive medical devices available for home detection of AF by analyzing cardiac activity through ECG or photoplethysmography (PPG). The review covers the technologies underlying single-lead ECG acquisition and PPG sensors, and describes how these are used, also in combination, in home-use medical devices (including smartwatches and wristbands).

EXPERT OPINION

Single-lead ECG and PPG technologies in consumer electronics have revolutionized AF detection, making it more accessible and convenient for patients. Despite some limitations in signal quality and diagnostic scope, these devices offer significant benefits for early AF detection and management. The use of wearable devices, including smartwatches and wristbands, for heart activity monitoring represents a promising advancement in patient-lead healthcare, potentially leading to better outcomes through timely medical intervention and improved patient engagement in managing their condition.

Development and validation of a machine learning model for diagnosis of ischemic heart disease using single-lead electrocardiogram parameters

BACKGROUND

Ischemic heart disease (IHD) impacts the quality of life and has the highest mortality rate of cardiovascular diseases globally.

AIM

To compare variations in the parameters of the single-lead electrocardiogram (ECG) during resting conditions and physical exertion in individuals diagnosed with IHD and those without the condition using vasodilator-induced stress computed tomography (CT) myocardial perfusion imaging as the diagnostic reference standard.

METHODS

This single center observational study included 80 participants. The participants were aged ≥ 40 years and given an informed written consent to participate in the study. Both groups, G1 (n = 31) with and G2 (n = 49) without post stress induced myocardial perfusion defect, passed cardiologist consultation, anthropometric measurements, blood pressure and pulse rate measurement, echocardiography, cardio-ankle vascular index, bicycle ergometry, recording 3-min single-lead ECG (Cardio-Qvark) before and just after bicycle ergometry followed by performing CT myocardial perfusion. The LASSO regression with nested cross-validation was used to find the association between Cardio-Qvark parameters and the existence of the perfusion defect. Statistical processing was performed with the R programming language v4.2, Python v.3.10 [^R], and Statistica 12 program.

RESULTS

Bicycle ergometry yielded an area under the receiver operating characteristic curve of 50.7% [95% confidence interval (CI): 0.388-0.625], specificity of 53.1% (95%CI: 0.392-0.673), and sensitivity of 48.4% (95%CI: 0.306-0.657). In contrast, the Cardio-Qvark test performed notably better with an area under the receiver operating characteristic curve of 67% (95%CI: 0.530-0.801), specificity of 75.5% (95%CI: 0.628-0.88), and sensitivity of 51.6% (95%CI: 0.333-0.695).

CONCLUSION

The single-lead ECG has a relatively higher diagnostic accuracy compared with bicycle ergometry by using machine learning models, but the difference was not statistically significant. However, further investigations are required to uncover the hidden capabilities of single-lead ECG in IHD diagnosis.

Cardiovascular Risk Assessment and Prevention in Cardio-Oncology: Beyond Traditional Risk Factors

This review goes beyond traditional approaches in cardio-oncology, highlighting often-neglected factors impacting patient care. Social determinants, environment, health care access, and gut microbiome significantly influence patient outcomes. Powerful tools like multi-omics and wearable technologies offer deeper insights into real-world experiences. The future lies in integrating these advancements with established practices to achieve precision cardio-oncology care. By crafting tailored therapies and continuously updating comprehensive management plans based on real-time data, we can unlock the full potential of personalized care for all patients.

Bridging the Gaps in Atrial Fibrillation Management in the Emergency Department

Atrial fibrillation (AF) frequently presents in emergency departments (EDs), contributing significantly to adverse cardiovascular outcomes. Despite established guidelines, ED management of AF often varies, revealing important gaps in care. This review addresses specific challenges in AF management for patients in the ED, including the nuances of rate versus rhythm control, the timing of anticoagulation initiation, and patient disposition. The updated 2024 European Society of Cardiology (ESC) guidelines advocate early rhythm control for select patients while recommending rate control for others; however, uncertainties persist, particularly regarding these strategies' long-term impact on outcomes. Stroke prevention through timely anticoagulation remains crucial, though the ideal timing, especially for new-onset AF, needs further research. Additionally, ED discharge protocols and follow-up care for AF patients are often inconsistent, leaving many without proper long-term management. Integration of emerging therapies, including direct oral anticoagulants and advanced antiarrhythmic drugs, shows potential but remains uneven across EDs. Innovative multidisciplinary models, such as "AF Heart Teams" and observation units, could enhance care but face practical challenges in implementation. This review underscores the need for targeted research to refine AF management, optimize discharge protocols, and incorporate novel therapies effectively. Standardizing ED care for AF could significantly reduce stroke risk, lower readmission rates, and improve overall patient outcomes.

Relative utility of portable ECG devices in capturing arrhythmias in athletes

INTRODUCTION

Traditional monitoring of athletes with cardiac symptoms is limited due to sport-specific considerations and the intermittent nature of symptoms. Some portable electrocardiogram (ECG) devices may have more diagnostic utility than traditional monitoring. Their accuracy, advantages, and limitations should be considered when a clinician is considering the most appropriate device for investigation of an athlete's symptoms.

AREAS COVERED

There are six main categories of portable ECG devices: smartwatches, handheld devices, mobile cardiac telemetry (MCT), patches, rings, and chest sensors. The aim of this review is to highlight to a clinician the potential benefits of some devices over others to assist the physician in identifying the most appropriate device. We present peer-reviewed literature on the accuracy of each type of device along with advantages and limitations.

EXPERT OPINION

For a user-initiated capture of an ECG, smartwatches and handheld devices are easy to use and supported by peer-reviewed literature. Rings can also provide a user-initiated ECG, though there is limited evidence to support their usage. For continuous monitoring, patches and MCT are both useful, though there is limited access to these devices. Chest sensors show some promise, although access is currently limited in some countries.

Impact of Wearable Technology on Heart Failure Management

BACKGROUND

Heart failure (HF) is a chronic and progressive condition that its management presents significant challenges in both clinical settings and patient self-care. Recent advances in wearable technology offer promising solutions to these challenges by enabling continuous monitoring, early detection of clinical deterioration, and personalized care. This review aims to critically evaluate the impact of wearable technology on HF management Materials and Methods: This narrative systematic review was conducted across multiple databases, including PubMed, Web of Science, and the Cochrane Library, to identify relevant studies published between 2010 and 2024. Studies on wearable devices for HF management and monitoring were included if they reported on clinical trials and provided data on integration into clinical workflows. Studies on other conditions or without original research data or Non-English papers were excluded.

RESULTS

Nine studies were evaluated in this study that were focusing on a variety of technologies ranging from consumer-grade fitness trackers to specialized bioimpedance sensors and wearable cardioverter-defibrillators. These studies demonstrate the potential of wearables to continuously monitor important health metrics, which can lead to early intervention and personalized care. However, there are still challenges to be addressed, including concerns about data accuracy, patient adherence, small sample sizes, and the incorporation of wearable data into clinical practice. While consumer devices are more accessible, their accuracy in a clinical setting is uncertain, while more advanced devices like the "Volum" monitor and BioZ sensors show promise but require further validation.

CONCLUSION

This review highlights the growing importance of wearable technologies in HF management, actionable insights that can prevent disease progression. However, significant challenges remain, including the need for further validation, device optimization, and data standardization before routine clinical practice. Future advancements should focus on improving device accuracy, patient adherence, and data security, while ensuring equitable access to these technologies.

Standardized assessment of evidence supporting the adoption of mobile health solutions: A Clinical Consensus Statement of the ESC Regulatory Affairs Committee: Developed in collaboration with the European Heart Rhythm Association (EHRA), the Association of Cardiovascular Nursing & Allied Professions (ACNAP) of the ESC, the Heart Failure Association (HFA) of the ESC, the ESC Young Community, the ESC Working Group on e-Cardiology, the ESC Council for Cardiology Practice, the ESC Council of Cardio-Oncology, the ESC Council on Hypertension, the ESC Patient Forum, the ESC Digital Health Committee, and the European Association of Preventive Cardiology (EAPC)

Mobile health (mHealth) solutions have the potential to improve self-management and clinical care. For successful integration into routine clinical practice, healthcare professionals (HCPs) need accepted criteria helping the mHealth solutions' selection, while patients require transparency to trust their use. Information about their evidence, safety and security may be hard to obtain and consensus is lacking on the level of required evidence. The new Medical Device Regulation is more stringent than its predecessor, yet its scope does not span all intended uses and several difficulties remain. The European Society of Cardiology Regulatory Affairs Committee set up a Task Force to explore existing assessment frameworks and clinical and cost-effectiveness evidence. This knowledge was used to propose criteria with which HCPs could evaluate mHealth solutions spanning diagnostic support, therapeutics, remote follow-up and education, specifically for cardiac rhythm management, heart failure and preventive cardiology. While curated national libraries of health apps may be helpful, their requirements and rigour in initial and follow-up assessments may vary significantly. The recently developed CEN-ISO/TS 82304-2 health app quality assessment framework has the potential to address this issue and to become a widely used and efficient tool to help drive decision-making internationally. The Task Force would like to stress the importance of co-development of solutions with relevant stakeholders, and maintenance of health information in apps to ensure these remain evidence-based and consistent with best practice. Several general and domain-specific criteria are advised to assist HCPs in their assessment of clinical evidence to provide informed advice to patients about mHealth utilization.

A New Remote Monitoring System: Evaluation of the Efficiency and Accuracy of the Smart Emergency Medical System-Health Internet of Things Device

BACKGROUND

The remote medical monitoring system can facilitate monitoring patients with cardiac arrhythmia, and consequently, reduce mortality and complications in individuals requiring emergency interventions. Hence, it is necessary to evaluate new telemedicine devices and compare them with standard devices. Therefore, this study aimed to evaluate and compare the new remote monitoring system, Smart Emergency Medical System-Health Internet of Things (SEMS-HIOT) developed by the Health Technology Development Centre of Babol University of Medical Sciences on patients with different cardiac arrhythmias and compare it with the standard device.

MATERIALS AND METHODS

In this case-control study, 60 patients were divided into the six most common arrhythmia groups (n=10 per each group and equal gender) as atrial fibrillation, ventricular tachycardia, paroxysmal supraventricular tachycardia, premature ventricular contractions, atrial tachycardia, and premature atrial contractions. Also, 20 healthy individuals (including 10 men and 10 women) without any arrhythmia (normal rhythm) were considered as the control group. Three similar SEMS-HIOT devices were used as test devices and a standard cardiac monitoring device as the control device. The clinical parameters, including heart rate, pulse rate, oxygen saturation, body temperature, and cardiac electrical activity via electrocardiogram (ECG) lead-II were recorded.

RESULTS

Findings showed that the performance of the SEMS-HIOT test device was similar and in the same range for all indices in each group and there were no significant differences compared to the performance of the control device (P0.05). Also, the ECG records measured with SEMS-HIOT and standard device indicate no significant differences (P0.05).

CONCLUSION

Our study showed that the cardiac indices as well as ECG findings, which were measured with SEMS-HIOT and common standard devices confirmed the accuracy and reliability of the new telematics device for monitoring patients with cardiac diseases.

Comparison of Postoperative Continuous Wireless Cardiac Rhythm Monitoring with Traditional Telemetry in Cardiac Surgery Patients: the SMART-TEL Study

Telemetry monitoring (conventional cardiac monitoring system [CCMS]) is a universal method for postoperative arrhythmia detection; however, the clinical challenge of alarm fatigue, primarily associated with noise or cable disconnections, persists. The introduction of wireless continuous cardiac monitoring (WCCM) represents a potential solution to enhance recording fidelity. Patients were simultaneously outfitted with both a monitoring device considered the standard of care and a novel adhesive wireless patch. A 48-h cardiac monitoring session with the two devices occurred after cardiac surgery in a unit equipped with a telemetry system. A total of 53 patients with a mean age of 60 ± 17 years were included in the trial. The number of events detected by the two systems was significantly different at 190 versus 174 for the CCMS and the WCCM system, respectively (P < .05). However, the percentage of agreement was not significantly different at 91% versus 88% (P = .37). Events were classified as follows: pause (2 events, 1%), atrial or premature ventricular contractions (18 events, 11%), atrial flutter or fibrillation (76 events, 45%), bradycardia (12 events, 7%), and tachycardia (61 events, 36%). False alarms were significantly more frequent with the CCMS (n = 21) than with the WCCM system (n = 5; P = .002). The study successfully demonstrated the feasibility and usability of wireless monitoring for patients requiring telemetry. The overall results are compelling, as the WCCM system performed satisfactorily, achieving results comparable to those obtained with the CCMS, even with significantly fewer false alarms.

Wearable Sensors in Other Medical Domains with Application Potential for Orthopedic Trauma Surgery-A Narrative Review

The use of wearable technology is steadily increasing. In orthopedic trauma surgery, where the musculoskeletal system is directly affected, focus has been directed towards assessing aspects of physical functioning, activity behavior, and mobility/disability. This includes sensors and algorithms to monitor real-world walking speed, daily step counts, ground reaction forces, or range of motion. Several specific reviews have focused on this domain. In other medical fields, wearable sensors and algorithms to monitor digital biometrics have been used with a focus on domain-specific health aspects such as heart rate, sleep, blood oxygen saturation, or fall risk. This review explores the most common clinical and research use cases of wearable sensors in other medical domains and, from it, derives suggestions for the meaningful transfer and application in an orthopedic trauma context.

Remote monitoring of atrial fibrillation recurrence using mHealth technology (REMOTE-AF)

Aims

This proof-of-concept study sought to evaluate changes in heart rate (HR) obtained from a consumer wearable device and compare against implantable loop recorder (ILR)-detected recurrence of atrial fibrillation (AF) and atrial tachycardia (AT) after AF ablation.

Methods and results

REMOTE-AF (NCT05037136) was a prospectively designed sub-study of the CASA-AF randomized controlled trial (NCT04280042). Participants without a permanent pacemaker had an ILR implanted at their index ablation procedure for longstanding persistent AF. Heart rate and step count were continuously monitored using photoplethysmography (PPG) from a commercially available wrist-worn wearable. Photoplethysmography-recorded HR data were pre-processed with noise filtration and episodes at 1-min interval over 30 min of HR elevations (Z-score = 2) were compared with corresponding ILR data. Thirty-five patients were enrolled, with mean age 70.3 ± 6.8 years and median follow-up 10 months (interquartile range 8-12 months). Implantable loop recorder analysis revealed 17 out of 35 patients (49%) had recurrence of AF/AT. Compared with ILR recurrence, wearable-derived elevations in HR ≥ 110 beats per minute had a sensitivity of 95.3%, specificity 54.1%, positive predictive value (PPV) 15.8%, negative predictive value (NPV) 99.2%, and overall accuracy 57.4%. With PPG-recorded HR elevation spikes (non-exercise related), the sensitivity was 87.5%, specificity 62.2%, PPV 39.2%, NPV 92.3%, and overall accuracy 64.0% in the entire patient cohort. In the AF/AT recurrence only group, sensitivity was 87.6%, specificity 68.3%, PPV 53.6%, NPV 93.0%, and overall accuracy 75.0%.

Conclusion

Consumer wearable devices have the potential to contribute to arrhythmia detection after AF ablation.

Study Registration

ClinicalTrials.gov Identifier: NCT05037136 https://clinicaltrials.gov/ct2/show/NCT05037136.

Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.

Navigating the Role of Smartwatches in Cardiac Fitness Monitoring: Insights From Physicians and the Evolving Landscape

Alongside the advancement of technology, wearable devices like smartwatches have widely been used for monitoring heartbeat, SpO2, EKG, and pacemaker activity. However, the global question is- can they be as effective as our standard diagnostic tests- electrocardiogram and echocardiography? Reported in the studies, smartwatches to the gold standard Holter monitoring for recognizing irregular pulse showed good sensitivity (98.2%), specificity (98.1%), and accuracy (98.1%). Smartwatches can be good enough for helping people get long-term monitoring of cardiac fitness and early diagnosis of atrial fibrillation but physicians shouldn't completely rely on them and perform standard investigations once the patient with symptoms visits them. We are also concerned that there must be certain rules and regulations for FDA approval of smartwatches to maintain standard criteria before they are released in the market.

Sports Heart Monitors as Reliable Diagnostic Tools for Training Control and Detecting Arrhythmias in Professional and Leisure-Time Endurance Athletes: An Expert Consensus Statement

There are countless types of portable heart rate monitoring medical devices used variously by leisure-time exercisers, professional athletes, and chronically ill patients. Almost all the currently used heart rate monitors are capable of detecting arrhythmias, but this feature is not widely known or used among their millions of consumers. The aims of this paper were as follows: (1) to analyze the currently available sports heart rate monitors and assess their advantages and disadvantage in terms of heart rate and rhythm monitoring in endurance athletes; (2) to discuss what types of currently available commercial heart rate monitors are most convenient/adjustable to the needs of different consumers (including occasionally physically active adults and cardiac patients), bearing in mind the potential health risks, especially heart rhythm disturbances connected with endurance training; (3) to suggest a set of "optimal" design features for next-generation smart wearable devices based on the consensus opinion of an expert panel of athletes, coaches, and sports medicine doctors. Ninety-two experts aged 20 years and over, involved in endurance sports on a daily basis, were invited to participate in consensus-building discussions, including 56 long-distance runners, 18 cyclists, nine coaches, and nine physicians (sports medicine specialists, cardiologists, and family medicine doctors). The overall consensus endorsed by these experts indicates that the "optimal" sports heart rate monitor should be a one-piece device of the smartwatch type (with two or more electrodes), with integrated smartphone features, and able to collect and continually transmit data without exhibiting artifacts. It should continuously record at least a single-lead electrocardiography, send an alert after an unexpected fall, be of reasonable weight, come at an affordable price, and be user friendly.

A Compact Dual-Band Millimeter Wave Antenna for Smartwatch and IoT Applications with Link Budget Estimation

Advancement in smartwatch sensors and connectivity features demands low latency communication with a wide bandwidth. ISM bands below 6 GHz are reaching a threshold. The millimeter-wave (mmWave) spectrum is the solution for future smartwatch applications. Therefore, a compact dual-band antenna operating at 25.5 and 38 GHz is presented here. The characteristics mode theory (CMT) aids the antenna design process by exciting Mode 1 and 2 as well as Mode 1-3 at their respective bands. In addition, the antenna structure generates two traverse modes, TM10 and TM02, at the lower and higher frequency bands. The antenna measured a bandwidth (BW) of 1.5 (25-26.5 GHz) and 2.5 GHz (37-39.5 GHz) with a maximum gain of 7.4 and 7.3 dBi, respectively. The antenna performance within the watch case (stainless steel) showed a stable |S11| with a gain improvement of 9.9 and 10.9 dBi and a specific absorption rate (SAR) of 0.063 and 0.0206 W/kg, respectively, at the lower and higher bands. The link budget analysis for various rotation angles of the watch indicated that, for a link margin of 20 dB, the antenna can transmit/receive 1 Gbps of data. However, significant fading was noticed at certain angles due to the shadowing effect caused by the watch case itself. Nonetheless, the antenna has a workable bandwidth, a high gain, and a low SAR, making it suitable for smartwatch and IoT applications.

Artificial Intelligence for Risk Assessment on Primary Prevention of Coronary Artery Disease

Purpose of Review

Coronary artery disease (CAD) is a common and etiologically complex disease worldwide. Current guidelines for primary prevention, or the prevention of a first acute event, include relatively simple risk assessment and leave substantial room for improvement both for risk ascertainment and selection of prevention strategies. Here, we review how advances in big data and predictive modeling foreshadow a promising future of improved risk assessment and precision medicine for CAD.

Recent Findings

Artificial intelligence (AI) has improved the utility of high dimensional data, providing an opportunity to better understand the interplay between numerous CAD risk factors. Beyond applications of AI in cardiac imaging, the vanguard application of AI in healthcare, recent translational research is also revealing a promising path for AI in multi-modal risk prediction using standard biomarkers, genetic and other omics technologies, a variety of biosensors, and unstructured data from electronic health records (EHRs). However, gaps remain in clinical validation of AI models, most notably in the actionability of complex risk prediction for more precise therapeutic interventions.

Summary

The recent availability of nation-scale biobank datasets has provided a tremendous opportunity to richly characterize longitudinal health trajectories using health data collected at home, at laboratories, and through clinic visits. The ever-growing availability of deep genotype-phenotype data is poised to drive a transition from simple risk prediction algorithms to complex, “data-hungry,” AI models in clinical decision-making. While AI models provide the means to incorporate essentially all risk factors into comprehensive risk prediction frameworks, there remains a need to wrap these predictions in interpretable frameworks that map to our understanding of underlying biological mechanisms and associated personalized intervention. This review explores recent advances in the role of machine learning and AI in CAD primary prevention and highlights current strengths as well as limitations mediating potential future applications.

The Utility of a Novel Electrocardiogram Patch Using Dry Electrodes Technology for Arrhythmia Detection During Exercise and Prolonged Monitoring: Proof-of-Concept Study

BACKGROUND

Accurate detection of myocardial ischemia and arrhythmias during free-living exercise could play a pivotal role in screening and monitoring for the prevention of exercise-related cardiovascular events in high-risk populations. Although remote electrocardiogram (ECG) solutions are emerging rapidly, existing technology is neither designed nor validated for continuous use during vigorous exercise.

OBJECTIVE

In this proof-of-concept study, we evaluated the usability, signal quality, and accuracy for arrhythmia detection of a single-lead ECG patch platform featuring self-adhesive dry electrode technology in individuals with chronic coronary syndrome. This sensor was evaluated during exercise and for prolonged, continuous monitoring.

METHODS

We recruited a total of 6 consecutive patients with chronic coronary syndrome scheduled for an exercise stress test (EST) as part of routine cardiac follow-up. Traditional 12-lead ECG recording was combined with monitoring with the ECG patch. Following the EST, the participants continuously wore the sensor for 5 days. Intraclass correlation coefficients (ICC) and Wilcoxon signed rank tests were used to assess the utility of detecting arrhythmias with the patch by comparing the evaluations of 2 blinded assessors. Signal quality during EST and prolonged monitoring was evaluated by using a signal quality indicator. Additionally, connection time was calculated for prolonged ECG monitoring. The comfort and usability of the patch were evaluated by a web-based self-assessment questionnaire.

RESULTS

A total of 6 male patients with chronic coronary syndrome (mean age 69.8, SD 6.2 years) completed the study protocol. The patch was worn for a mean of 118.3 (SD 5.6) hours. The level of agreement between the patch and 12-lead ECG was excellent for the detection of premature atrial contractions and premature ventricular contractions during the whole test (ICC=0.998, ICC=1.000). No significant differences in the total number of premature atrial contractions and premature ventricular contractions were detected neither during the entire exercise test (P=.79 and P=.18, respectively) nor during the exercise and recovery stages separately (P=.41, P=.66, P=.18, and P=.66). A total of 1 episode of atrial fibrillation was detected by both methods. Total connection time during recording was between 88% and 100% for all participants. There were no reports of skin irritation, erythema, or pain while wearing the patch.

CONCLUSIONS

This proof-of-concept study showed that this innovative ECG patch based on self-adhesive dry electrode technology can potentially be used for arrhythmia detection during vigorous exercise. The results suggest that the wearable patch is also usable for prolonged continuous ECG monitoring in free-living conditions and can therefore be of potential use in cardiac rehabilitation and tele-monitoring for the prevention of exercise-related cardiovascular events. Future efforts will focus on optimizing signal quality over time and conducting a larger-scale validation study focusing on both arrhythmia and ischemia detection.

An overview of the electrocardiographic monitoring devices in sports cardiology: Between present and future

BACKGROUND

Athletes represent a mainly healthy population, which however could be considered at risk of major arrhythmic events, especially in case of undiagnosed cardiomyopathies. For this reason, the periodical sports medicine examination and the electrocardiography are essential tools in the cardiovascular screening, even though they do not always succeed in identifying rhythm disturbances, particularly when asymptomatic or rarely symptomatic.

HYPOTHESIS

Prolonged cardiac monitoring often enables clinicians to stratify the arrhythmic risk and reach the diagnosis. The technological progress of the last decades has produced an always-increasing number of heart rhythm monitoring devices, starting from the 24-hour electrocardiogram Holter monitoring and ending with the wide world of wearable devices.

METHODS

In the literature, the extreme utility of this equipment in the patients affected by cardiovascular diseases and in the general population is well established. On the contrary, athletes-based randomized trials or large-scale epidemiological studies targeting the frequency of cardiac symptoms and the use of cardiac monitoring are missing, while an ever-growing number of case series and small observational studies are flourishing in recent years.

RESULTS

The present review showcases the available electrocardiographic monitoring options, principally in the medical setting, listing their characteristics, their indications, their supporting evidence, and their general pros and cons.

CONCLUSIONS

The ultimate goal of this review is guiding physicians through the wide variety of heart rhythm monitoring options in the specific subfield of sports cardiology, when an arrhythmia is suspected in an athlete, to tailor the diagnostic process and favor the best diagnostic accuracy.

The use of digital health in heart rhythm care

INTRODUCTION

Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to improve patient health and health care services. With the growing use of wearables, artificial intelligence, machine learning, and other novel technologies, digital health is particularly relevant to the field of cardiac arrhythmias, with roles pertinent to education, prevention, diagnosis, management, prognosis, and surveillance.

AREAS COVERED

This review summarizes information on the clinical use of digital health technology in arrhythmia care and discusses its opportunities and challenges.

EXPERT OPINION

Digital health has begun to play an essential role in arrhythmia care regarding diagnostics, long-term monitoring, patient education and shared decision making, management, medication adherence, and research. Despite remarkable advances, integrating digital health technologies into healthcare faces challenges, including patient usability, privacy, system interoperability, physician liability, analysis and incorporation of the huge amount of real-time information from wearables, and reimbursement. Successful implementation of digital health technologies requires clear objectives and deep changes to existing workflows and responsibilities.

Investigation of Non-contact Electrodes for Electrocardiogram Monitoring

This work investigates the use of an active noncontact electrode to monitor electrocardiogram (ECG) signals in the chest region of the human body across different interface materials. Non-contact electrodes provide an advantage over wet gel electrodes as they do not require direct contact with the skin which can lead to skin irritation. The key aspects and parameters of non-contact electrodes were discussed. Additionally, a printed circuit board (PCB) electrode was designed and prototyped. Experimental evaluations were performed to demonstrate the feasibility of the design as well as the impact of various interface materials. Results showed that R-peaks can be detected through all materials tested. The highest noise levels were observed in polyester, resulting in the highest signal standard deviation, followed by merino and cotton. The patch sensor with just a solder mask as an insulation layer provided the clearest ECG signal, with 100% accuracy on Rpeak detection.Clinical relevance- Non-contact electrodes offer a more comfortable solution for long-term heart monitoring with minimal discomfort due to less skin irritation when compared to conventional electrodes.

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

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

Cardiac Rhythm Monitoring Using Wearables for Clinical Guidance before and after Catheter Ablation

Mobile health technologies are gaining importance in clinical decision-making. With the capability to monitor the patient's heart rhythm, they have the potential to reduce the time to confirm a diagnosis and therefore are useful in patients eligible for screening of atrial fibrillation as well as in patients with symptoms without documented symptom rhythm correlation. Such is crucial to enable an adequate arrhythmia management including the possibility of a catheter ablation. After ablation, wearables can help to search for recurrences, in symptomatic as well as in asymptomatic patients. Furthermore, those devices can be used to search for concomitant arrhythmias and have the potential to help improving the short- and long-term patient management. The type of wearable as well as the adequate technology has to be chosen carefully for every situation and every individual patient, keeping different aspects in mind. This review aims to describe and to elaborate a potential workflow for the role of wearables for cardiac rhythm monitoring regarding detection and management of arrhythmias before and after cardiac electrophysiological procedures.