{
  "abstract": "Introduction The increasing prevalence of arrhythmias, particularly atrial fibrillation (AF), presents a significant public health challenge. Early detection of arrhythmias is essential to mitigate the risks of stroke and other cardiovascular complications. Wearable devices, especially smartwatches, have emerged as effective tools for continuous monitoring of arrhythmias, providing a valuable solution for detecting infrequent events. These devices facilitate early detection by reversing the traditional healthcare model, where medical review precedes diagnostic monitoring. This shift helps bridge the gap between clinical visits and enables real-time data sharing between patients and healthcare providers.Methods This review examines the current landscape of smartwatches for arrhythmia detection. It focuses on the technologies utilized in these devices, such as photoplethysmography (PPG) and electrocardiography (ECG), their applications in arrhythmia detection, costs, licences, and clinical effectiveness, as evidenced by various studies and trials. Smartwatches from companies like Apple, Garmin, Samsung, and Huawei, incorporating PPG and ECG technologies, are assessed for their performance in detecting arrhythmias, particularly AF.Results Smartwatches equipped with PPG and ECG sensors have shown substantial accuracy in detecting AF, with sensitivity and specificity values exceeding 90%. For example, the Apple heart study showed Apple Watch’s positive predictive value (PPV) of 84% in detecting AF. Other smartwatches, such as the Garmin Venu series has PPV of 90%, Galaxy Watch by Samsung proved PPV of 95%, and Huawei Watch showed PPV of 91.6% in mAFA-II trial. Despite their effectiveness, these devices can lead to false positives and overdiagnosis, which may result in unnecessary anxiety and healthcare visits. While their performance in detecting AF is well-established, smartwatches have yet to be extensively validated for detecting other arrhythmias, limiting their broader clinical application.Conclusions Smartwatches represent a transformative shift in arrhythmia detection and management, and their diagnostic accuracy for AF is promising. However, challenges such as the risk of overdiagnosis, limited validation for a broader spectrum of arrhythmias, and difficulties with integration into established healthcare systems remain. To fully realize their potential, future advancements should focus on enhancing detection algorithms, expanding the range of detectable arrhythmias, and driving cost reductions. Additionally, the inclusion of measurements for blood pressure, cardiac output, or suitable surrogates would significantly improve the evaluation of arrhythmias and provide critical insights for diagnosing syncope.Abstract 4-001 Table 1 Manufac-turer MODEL* FDA CE Cost** AF Detection Automatic-ally*** Core Study PPG ECG Apple Inc • Series 4,5,6,7,8,9,10• ULTRA 1 & 2 ✓ ✓ £300 -£800 ✓ Apple Heart Study ✓ ✓✓ Samsung electronics • Galaxy watch Active 2.• Galaxy Watch 3,4,5,6,7 ✓ ✓ £250 -£400 ✓ - ✓ ✓✓ Huawei Technologies Co • GT 3 Pro• Gt 5 pro• 4 pro space Edition ✓ £300 - £500 ✓ mAFA-II Trial ✓ ✓✓✓ Garmin Ltd • Venu 2 plus• Venu 3 Series• Epix Pro• Fenix 7 Pro ✓ £350 - £700 ✓ - ✓ ✓✓✓✓ Abstract 4-001 Figure 1",
  "authors": [
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK",
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK",
        "NIHR Leicester Cardiovascular Biomedical Research Centre, Leicester, UK"
      ],
      "name": "Ahmed Abdelrazik"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK",
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK"
      ],
      "name": "Mahmoud Eldesouky"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK"
      ],
      "name": "Ibrahim Antoun"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK",
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK"
      ],
      "name": "Edward Yan Ming Lau"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK"
      ],
      "name": "Safiyyah A Suleman"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK"
      ],
      "name": "Abdulmalik Koya"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK",
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK",
        "NIHR Leicester Cardiovascular Biomedical Research Centre, Leicester, UK",
        "Leicester British Heart Foundation Centre of Research Excellence, Leicester, UK"
      ],
      "name": "Abdulmalik Koya"
    },
    {
      "affiliations": [
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK"
      ],
      "name": "Ivelin Koev"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK",
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK"
      ],
      "name": "Zakariyya Vali"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK"
      ],
      "name": "James Donaldson"
    },
    {
      "affiliations": [
        "Department of Cardiovascular Sciences, University of Leicester, Leicester, UK",
        "Department of Cardiology, University Hospitals of Leicester NHS Trust, Leicester, UK",
        "NIHR Leicester Cardiovascular Biomedical Research Centre, Leicester, UK",
        "Leicester British Heart Foundation Centre of Research Excellence, Leicester, UK"
      ],
      "name": "G André Ng"
    }
  ],
  "title": "4-001 Smartwatches for arrhythmia detection: a review of current technologies and clinical applications",
  "uid": "a1ba4b5c-caf7-59ec-b633-4a4f30c0c06f"
}