Introduction

A cardiac arrhythmia is an irregular heartbeat. The most common way of classifying them is based on the rate of conduction: bradyarrhythmia with a heart rate of less than 60 beats per minute (bpm) and tachyarrhythmia with a heart rate greater than 100 bpm.¹ It may lead to a life-threatening stroke, heart failure, or cardiac arrest. It is anticipated that 1.5%-5% of the general population would experience arrhythmias, with atrial fibrillation being the most prevalent.² It may be difficult to determine the true prevalence of arrhythmias because they can be paroxysmal and develop with or without symptoms at all. The overall presence of arrhythmia is associated with a higher degree of morbidity and mortality.¹ Accurate detection is related to the prevention of severe outcomes, and thus electrocardiogram (ECG) is an essential tool in clinical practice.

Electrocardiogram is one of the non-invasive diagnostic means that provides rapid identification for many heart diseases, especially the electro-cardiac arrhythmias and acute coronary syndrome.^3-5 Diagnosis of any cardiac arrhythmia requires ECG confirmation to determine the severity, implications, and available treatments. Traditional short-term cardiac monitors cannot provide adequate information for patients who have infrequent and temporary symptoms or who suffer from paroxysmal atrial fibrillation (AF) with or without symptoms.⁶ The standard 12-lead ECG has a major limitation in that it needs exact electrode placement, which makes it challenging for patients to record at home without medical assistance. A method for home ECG recording without professional help would be highly beneficial.⁷

However, with the emergence of smartphone-based electrocardiogram devices in recent times, this field has been revolutionized by offering a portable, inexpensive, and practical solution for the detection of arrhythmias in real time. Continuous monitoring, ease of use, and broad accessibility offered by these devices are essential for effective arrhythmia management. These smartphone ECG devices are useful in the detection of various cardiac rhythm abnormalities. The use of the AliveCor Kardia smartphone ECG device was demonstrated by Jewson et al⁸ for diagnosing exercise-related arrhythmias in athletes, with their obtained ECG traces during highly vigorous exercise, where traditional monitors would fail. Issa et al⁹ presented a deep neural network model for the classification of ECG beat classes, achieving high levels of accuracy and thus being one of the advanced machine learning techniques to show potential for improvement in diagnostic capabilities using single-lead mobile ECG devices.

Recent advancements have increased the scope of these devices. For instance, Haseeb et al¹⁰ investigated the integration of artificial intelligence with smartphone ECG devices and observed significant improvements in the accuracy of arrhythmia detection and predictive analytics. Similarly, benefits from real-time monitoring for patients with chronic cardiac conditions have been reviewed by Hossain et al¹¹, underscoring a reduction in emergency room visits and hospitalization due to timely interventions. Further, Zimetbaum and Nguyen¹² discussed the implications of mobile health technologies in chronic disease management, highlighting their role in patient empowerment and engagement.

The predictive capabilities of these devices were also demonstrated by some research. Gadaleta et al¹³ developed a deep-learning model for the prediction of near-term AF from ambulatory single-lead ECG recordings using AF-free ECG intervals, improving the accuracy of prediction by a significant margin over demographic metrics alone. More generally, Baman et al⁶ discussed the impact of mobile health (mHealth) devices, including smartphone ECGs, on the accessibility and lowering of costs associated with arrhythmia detection, despite limitations like motion artifact and the need to confirm the detected arrhythmias by ECG.

A smartphone-based ECG device’s accuracy in monitoring horse cardiac rhythms was demonstrated by Hothersall et al¹⁴ in veterinary medicine, indicating a wider range of applications beyond human medicine. Various large-scale screening studies, like Gruwez et al¹⁵ in Belgium, have demonstrated the therapeutic implications and viability of using smartphone-based devices for AF screening in the general population. Similarly, Rajakariar et al¹⁶ evaluated the AliveCor KardiaBand’s diagnostic accuracy for AF and emphasized the need for physician involvement to ensure proper diagnosis.

Portable ECG devices, such as the Apple Watch and Alivecor, are used for lead I testing, which assesses rhythm abnormalities like atrial fibrillation. To prevent false positives, high specificity and sensitivity are required. The Lead II or a rhythm strip is sufficient for diagnosing any cardiac arrhythmia. A smartphone-based portable ECG device (Spandan) that is capable of taking lead II and also 12 lead ECGs by using derived ECG methods. The Spandan portable ECG (Sunfox Technologies Pvt. Ltd.) device connects to a smartphone via an application interface, as shown in Figure 1. The test ECG device claims to evaluate cardiac arrhythmias.^17,18

In the context of smartphone-based electrocardiographic devices, Mahajan et al¹⁹ assessed the accuracy of the Spandan 12-lead smartphone ECG device in rhythm abnormality detection. Their study demonstrated that the Spandan ECG device had high sensitivity and specificity, like the standard 12-lead electrocardiogram, which opens a potential role for this tool to increase diagnostic accuracy in routine clinical practice. Their findings, therefore, provided a base for smartphone electrocardiographic devices in improving arrhythmia detection and management in clinical and non-clinical settings.²⁰

Various case reports illustrate the Spandan ECG device’s ability to detect early disease stages and prompt medical intervention. Singh et al²¹ reported a 54-year-old patient with chest heaviness and palpitations, for which Spandan ECG revealed anteroseptal and lateral wall ischemia, thus helping in ischemic heart disease management. Another case involved an 84-year-old female with several comorbidities who became confused as a result of ventricular premature contractions and AF. The device facilitated AF detection, leading to pacemaker implantation.²² Similarly, Spandan detected sinus rhythm with ventricular premature complexes in a 63-year-old patient with dyspnea, later diagnosed with atrial septal defect.²³ Chandola²⁴ reported Spandan ECG’s role in monitoring ventricular tachycardia and cardiac sarcoidosis, guiding timely defibrillator implantation. Additionally, Singh et al²⁵ identified Wolff-Parkinson-White syndrome during a routine health check-up. These cases underscore Spandan’s value as a point-of-care modality in enhancing cardiac diagnosis and management.

The study was designed to assess and validate Spandan lead II ECG interpretation in detecting cardiac arrhythmia accuracy by comparing its diagnostic performance with only lead II ECG strips from the Gold Standard ECG machines and diagnoses made by a cardiologist. This was done by evaluating the sensitivity, specificity, and overall accuracy of Spandan.

Methods

Study Design

The study has been designed with meticulous care: a single-blinded, cross-sectional, and observational inquiry. It is aimed at validating the accuracy of only Lead II of the Spandan 12 Lead ECG Machine interpretation for detecting cardiac arrhythmias, compared with a cardiologist’s diagnosis, and assessing the accuracy of Spandan ECG in the detection of arrhythmias when compared with only the lead II strip from the 12 Lead gold standard ECG machines.

Participants

The study cohort comprised 3000 individuals aged 20 years or older who had been selected from patients referred by doctors for ECG investigation in the ECG room. Patients with implanted pacemakers and those who reported baseline wandering and artifacts in the ECG reports were excluded from this analysis. Following the application of exclusion criteria, 2799 individuals were eligible for inclusion, ensuring a cohort representative of the target population.

Lead II Electrocardiogram Strips for Arrhythmia Detection

The comparison was performed between the Lead II ECG strip from the gold standard ECG machine and the Lead II ECG strip of the Spandan ECG device. While both devices are capable of recording a full 12-lead ECG, the analysis focused especially on the Lead II rhythm strip, which is capable of arrhythmia detection, including conditions such as AF, atrial ectopic beats, and other arrhythmias.⁹ Lead II acquisition is straightforward and can be performed even by untrained personnel, enhancing its practicality in diverse settings. To address potential discrepancies caused by dynamic ECG changes, the time interval between recordings from the 2 devices was strictly limited to no more than 10 minutes, thereby minimizing the risk of evaluation errors and ensuring a robust comparison.

Ethical Considerations

Although this study primarily evaluates the device’s diagnostic capabilities rather than making direct clinical decisions, it has been recognized that data from this study could inform future diagnostic or decision-support tools. The institution’s ethics board has been consulted, and while formal ethics approval was deemed unnecessary for this phase, ethical standards such as obtaining signed informed consent without recording patient names, anonymizing and encoding patient names on ECG reports, and Case Report Forms during data collection to ensure participant confidentiality will be adhered to. If the scope of the study evolves to involve clinical decision-making directly, ethics committee approval will be sought as appropriate.

Ethical Approval

Ethical considerations for this study were conducted under the guidance of the head of the Cardiology Department due to the non-interventional nature of the research and no clinical decisions or medications were administered based on the smartphone ECG device results. All clinical decisions were made by cardiologists using the gold standard ECG. As a result, local institutional ethics committee approval was not sought. The study was carried out in accordance with the principles of the Declaration of Helsinki.

Informed Consent

Before being included in the study, each participant provided their informed consent. Both verbally and in writing, participants received comprehensive information on the purpose, procedures, potential risks, and benefits associated with the study. Consent forms were designed to be easily understandable and included statements ensuring participants’ right to withdraw from the study at any time without any consequences to their medical care. Signed consent forms were collected and securely stored according to ethical guidelines.

Settings

This research was carried out in the ECG room at the local hospital from August 2, 2022 to June 2, 2023.

Supervision and Oversight

All tests and procedures were undertaken under the supervision of a cardiologist or an ECG technician to ensure uniformity in following laid-down protocols, introducing the least bias. With such conscientious supervision maintained, the data collected becomes more reliable and accurate, and the integrity of the research study is preserved.

Reference Standard

In this study, the reference standard used for the assessment of both the Spandan smartphone-based ECG device and the Gold Standard ECG machine was the cardiologist’s interpretation of arrhythmias. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy rates were calculated for reports of both devices to compare their diagnostic performance relative to the cardiologist’s interpretation. This approach provides an unbiased assessment of their ability to detect arrhythmias accurately in the study population.

Data Collection

The study will be conducted in 2 stages. In the first stage, consent forms will be collected from participants verbally and in writing. Field data collectors will fill out the Case Report Format (CRF) according to study protocols, which will be submitted to the principal investigator. The CRF contains information on diabetes history, smoking, current symptoms, implanted pacemakers, and any history of coronary intervention. The CRF assists the cardiologist in diagnosing the case appropriately. In the second stage, the ECG will be performed by the Gold standard ECG machine, followed by the lead II ECG test using the Spandan smartphone-based ECG device. Both ECG machines are equipped with computerized interpretation, and printed reports will be obtained.

Data Interpretation

A cardiologist would be assigned to provide a diagnosis for both Spandan and Gold standard ECG reports. The cardiologist would be blind computerized interpretations to avoid bias.

Timing Considerations

To mitigate this potential bias, a time interval of not more than 10 minutes between the Spandan system report and the Gold Standard ECG report will be observed. This temporal demarcation ensures an impartial and stringent assessment of diagnostic accuracy.

Both the gold standard ECG and the Spandan device performed simultaneous recordings in the majority of cases. However, the cases listed below experienced time discrepancies between the recordings due to factors such as patient overload and challenges like improper electrode adhesion caused by hair or oily skin.

As understood, the note highlights specific considerations for interpreting the results:

Statistical Analysis

The diagnostic accuracy of the 2 devices, Spandan and the gold standard, concerning recommending arrhythmia, was evaluated in this regard by sensitivity, specificity, PPV, NPV, F-Score, and Matthew’s correlation coefficient (MCC).

The F-score, or F1-score, measures a test’s accuracy, focusing on the balance between correctly identified positive cases—true positives (TP)—and misclassified cases, including false positives (FP) and false negatives (FN). It is calculated as shown in equation (1).

The F-score ranges from 0 to 1, where a value of 1 indicates perfect accuracy, meaning all true positives are identified without any false positives or false negatives, while a value of 0 represents the worst possible performance, with no true positives identified.

Matthew’s correlation coefficient is a metric for evaluating binary classification performance, accounting for TP, true negatives (TN), FP, and FN. It is calculated as shown in equation (2).

P-value ranges from −1 to +1, where +1 represents perfect agreement, 0 indicates random guessing, and −1 signifies total disagreement between predictions and actual outcomes.

Artificial Intelligence–Assisted Technologies: QuillBot, Draw.io.

Archival

The scanned ECG reports and all study-related documents will be kept in cloud storage for transparency purposes and future reference. Archiving this way ensures proper scrutiny and verification of the findings.

Technical Specifications of the Spandan Device

A description of the algorithms utilized by the device for arrhythmia detection (e.g., signal preprocessing, feature extraction, and decision logic), as outlined in Figure 4, was applied for analysis.

Results

In this study, the STARD (Standards for Reporting Diagnostic Accuracy Studies) guidelines were followed (as shown in Figure 5). These guidelines are based on diagnostic accuracy studies, which are designed to assess the performance of a diagnostic test or tool (Spandan smartphone-based ECG) by comparing its results with a reference or gold standard. This approach ensures the reliability and validity of the findings by adhering to a standardized framework for reporting diagnostic accuracy.

The study initially enlisted the participation of 3000 individuals between August 2, 2022, and June 2, 2023. Only 2799 individuals who fulfilled the inclusion criteria of the present study were invited to participate in the Arrhythmia screening study. Among them, 979 exhibited abnormalities, while 1820 displayed normal ECG readings. The cohort comprised 843 females and 1956 males, thus reflecting the gender distribution within the population. Adhering to hospital protocols, every patient referred by a doctor to the ECG room underwent an ECG procedure utilizing the Gold Standard ECG. In the specific context of this research endeavor, an additional ECG was recorded using a smartphone-based ECG device.

A comparative analysis of ECG tracings from both the Gold Standard machine and the Spandan smartphone-based lead II ECG device for the lead II test revealed substantial concordance. Most tracings displayed an excellent resemblance, with only minor differences that lacked diagnostic significance. Figures 6 and 7 visually exemplify this alignment, showcasing the Gold Standard ECG and the Spandan ECG of the same patient.

For instance, the computerized analysis of the Gold Standard ECG revealed atrial fibrillation. Next, the computerized interpretation by Spandan also showed atrial fibrillation, aligning the result with the Gold Standard ECG. A cardiologist, blinded to the computerized interpretations and origin of the reports, reviewed both sets of ECG tracings independently to avoid bias. This clinical interpretation was confirmed by the cardiologist as evidence of atrial fibrillation in the patient and further highlighted the potential diagnostic utility of the Spandan ECG device.

Among 979 abnormal cases, premature ventricular complexes (11.6%), sinus bradycardia (33.6%), and sinus tachycardia (41.2%) were most prevalent, and other different types of detected arrhythmias were outlined in Table 1.

Hypertension (24.7%) and CAD (36.37%) dominated participant comorbidities, highlighting a diverse clinical profile, as shown in Table 2.

Spandan ECG showed comparable accuracy to the gold standard ECG, with higher true positives and fewer false positives detected, as demonstrated in Table 3.

Spandan ECG had more specificity than the gold standard ECG (96.3% vs. 94.8%) and had a higher PPV (93.2% vs. 90.3%) while having equivalent sensitivity and negative predictive value, as presented in Table 4 and Figure 8.

The Spandan Lead II ECG performed better by achieving 96.0% accuracy, 93.2% precision, an F-score of 0.94, and a P = .913, for P > .001; it outperformed the Gold Standard ECG in all aspects, as shown in Figure 9 and Tables 5 and 6.

Among 2799 subjects, the prevalence of diabetes, hypertension, and smoking was analyzed. Higher male representation in both normal and abnormal groups is reported in Table 7.

Confounding Factors: Analysis of demographic variability (age, gender, comorbidity) and its influence on the results were described in Table 8. Environmental factors, such as patient movement, improper electrode placement, and electrical noise, can affect ECG recording quality in healthcare settings. Physical activity, like during stress tests, may introduce noise or arrhythmias, impacting device performance and interpretation accuracy.

A detailed comparison of the Spandan Smartphone ECG’s diagnostic performance with outcomes from prior research on cardiac arrhythmia detection was presented in Table 9.

Discussion

Principal Findings

To assess and validate the diagnostic performance of the Spandan lead II ECG device for the diagnosis of cardiac arrhythmias compared to the gold standard conventional ECG machine, diagnosis by the cardiologist. The Spandan ECG captured episodes of arrhythmias in the subject under continuous monitoring, each 10 seconds in duration. Data showed numerous forms of arrhythmic patterns; among the most common were Atrial Flutter, AF, Accelerated Junctional Rhythm, Atrial Tachycardia, Junctional Rhythm, Ventricular Ectopic, Sinus Bradycardia, and Sinus Tachycardia. The findings of this study underscore the clinical validity and reliability of lead II-based arrhythmia testing using the Spandan smartphone-based ECG device. These results demonstrate high sensitivity and specificity, with Spandan ECG achieving a sensitivity of 95.5% and a specificity of 96.3% in detecting cardiac arrhythmias compared to the gold standard ECG. These results highlight the robustness of Spandan ECG in accurately identifying rhythm abnormalities, reaffirming its clinical utility and correctness in arrhythmia detection.

Atrial fibrillation is the most prevalent persistent heart rhythm disorder in the general population, with a global community prevalence ranging from 0.5% to 5.5%.^28-31 Research conducted in India has revealed significant variations in AF prevalence, ranging from 0.1% to 1.6%.^32,33 This highlights the need for tools like the Spandan smartphone-based ECG, which can assist patients in early detection of arrhythmias in both clinical and non-clinical settings. In those with detected arrhythmias, timely intervention may help in altering treatment plans.

Comparison with the Existing Literature

In this study, there were 52 patients with 1^st Degree AV Block diagnosed, with a predominance of males (85%) and the most afflicted age group being individuals aged 60 and above. This study showed a high correlation between aging, diabetes, and 1^st AV Block. In diabetic individuals, a significantly higher ratio of developing 1^st AV Block was observed in males than in females. Previously, studies have shown an increased diabetes and an elevated risk for 3^rd Degree AV Block,^34-36 This study demonstrates that diabetes also elevates the risk of 1^st Degree AV Block. However, further research on larger populations is needed to validate these findings. The presence of 1^st Degree AV Block in high-risk groups highlights the importance of closer monitoring to prevent progression to severe arrhythmias.

Premature ventricular complexes were the most common arrhythmia identified, observed in 114 patients, with a higher prevalence among males and individuals aged 60 and above. Premature ventricular complexes were particularly frequent in patients with diabetes mellitus, with males again exhibiting a significantly higher risk than females. These findings align with the previous study by De Sensi et al (2022)³⁷, which reported that diabetes mellitus patients are more likely to experience PVCs.

Atrial fibrillation was observed in 68 patients in this study, with the condition primarily affecting older individuals, particularly those aged 60 and above, highlighting age as a significant risk factor. Additionally, males were slightly more affected than females. The study also identified hypertension as a key contributor to the risk of developing AF. These findings suggest that targeted screening for AF in hypertensive patients, especially in elderly males, could be beneficial for early diagnosis and effective management. Consistent with previous research, this study reinforces the association between hypertension and an increased risk of AF.^38,39

Although the gold standard 12-lead ECG has to be taken in clinical settings only and with considerable care towards electrode placement and requires medical assistance, the present device is helpful in remote locations by facilitating easy usability and portability, which aids in providing good monitoring irrespective of healthcare setup. Several prior studies agree with these conclusions by establishing that real-time arrhythmia detection is feasible in any type of healthcare environment, either in rural or in the urban setup.^40-42

Moreover, in a review by Bhavnani et al (2018)⁴³, the authors discussed the broader implications of mobile health technologies, underscoring the transformative potential of these tools in modern healthcare. These studies collectively support the notion that smartphone-based ECG devices, such as Spandan, are not only clinically viable but also highly beneficial in enhancing patient care through improved diagnostic accuracy and timely intervention.

Strengths and Limitations

Addressing Selection Bias

Scalability and Cost-Effectiveness

Clinical Significance

Our study demonstrates the clinical validity and usability of lead II-based arrhythmia testing using the Spandan smartphone-based ECG device. Achieving high accuracy, sensitivity, and specificity for the Spandan smartphone-based ECG device suggests that it is a very useful device for the early detection and diagnosis of cardiac arrhythmias in both hospital and non-hospital settings. Comprehensive smartphone-based ECGs from a non-hospital setup could perhaps facilitate timely diagnosis and management of patients with paroxysmal or asymptomatic arrhythmias. This could potentially reduce the burden on healthcare facilities and improve patient outcomes by providing continuous monitoring and early intervention.

Conclusion

The research thus showed that the Spandan, a smartphone-based ECG device, was effective, with high reliability in diagnosing cardiac arrhythmias. The device seems to be very sensitive and specific in detecting cardiac arrhythmias compared to the only Lead II ECG strip from the Gold standard ECG machine. With high sensitivity at 95.5% and specificity at 96.3%, Spandan ECG proved very effective in accurately determining rhythm abnormalities in a large cohort of 2799 participants. This arrhythmia study was conducted using a Lead II rhythm strip (Spandan ECG) rather than a 12-lead ECG (Spandan ECG). To reduce noise when analyzing with the Spandan ECG device, filters are used. In the case of single-lead analysis (Lead II), these filters may sometimes result in the absence of a P wave. When this occurs, a 12-lead Spandan ECG can be utilized for confirmation by comparing the results of 12 leads with Lead II, thereby improving diagnostic accuracy. Despite this, for point-of-care use, the Spandan Lead II test demonstrates a strong correlation in detecting arrhythmias, making it effective for quick assessments. Therefore, these findings underline the clinical validity of the arrhythmia test based on Lead II and establish Spandan ECG as a dependable tool for detecting arrhythmia.

Portability, ease of use, and cost-effectiveness in the scenarios of hospitals, ambulances, and remote areas make smartphone-based ECG devices like Spandan enhance their utility. This enables continuous monitoring and real-time detection of arrhythmias, which can enhance patient outcomes with timely diagnosis and intervention. Routine clinical use of Spandan ECG integration may reduce the burden on traditional ECG facilities with efforts toward making arrhythmia detection more accessible and efficient.

The large sample size and robust study methodology increase the weight of evidence from this study, making the results more reliable for clinical applications of Spandan ECG. Spandan Lead II ECG has been compared with others concerning its superior diagnostic accuracy; it has been one of the best-proven aids in better arrhythmia management.

In summary, the Spandan smartphone ECG-based lead II device provides practical and valuable solutions for diagnosing arrhythmias—highly accurate diagnostically with broad applicability. Its application in clinical and emergency settings helps improve the management of cardiac arrhythmias and, therefore, leads to better patient care and outcomes.

Footnotes

Ethics Committee Approval: Ethical considerations for this study were conducted under the guidance of the head of the Cardiology Department due to the non-interventional nature of the research and no clinical decisions or medications were administered based on the smartphone ECG device results. All clinical decisions were made by cardiologists using the gold standard 12-lead ECG. As a result, local institutional ethics committee approval was not sought. The study was carried out in accordance with the principles of the Declaration of Helsinki.

Informed Consent: Before being included in the study, each participant provided their informed consent. Both verbally and in written form.

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - S.M., S.G., Y.S.; Design - S.M., S.G., Y.S.; Supervision - S.G., S.M., T.B.; Resource - N.C., D.A., R.S.; Materials - S.M., N.C., D.A.; Data Collection and/or Processing - N.C., D.A., R.S.; Analysis and/or Interpretation - S.M., N.C., D.A.; Literature Search - N.C., D.A., T.B.; Writing - N.C., D.A., T.B.; Critical Reviews- S.M., N.C., Y.S.

Acknowledgments:

Department of Cardiology, Shri Mahant Indresh Hospital, Dehradun, India, and Sunfox Technologies Private Limited, Dehradun, India.

Declaration of Interests: The authors of this study declare that they have no conflicts of interest that could affect the objectivity, integrity, or impartiality of the research.

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