Rise of the smart device ECG and what it means for the general cardiologist

Bennett, Richard G.; French, A.

doi:10.1136/heartjnl-2019-315357

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…However, there are several barriers to overcome if such technology is to become the contemporary standard in arrhythmia detection. Current iterations of single-lead iECG devices are heavily reliant on symptoms of palpitations to trigger opportunistic screening, and consequently can overlook patients with paroxysmal arrhythmias 22. While alternative wearables using photoplethysmography (PPG) can provide continuous screening, accuracy is currently affected by motion artefact, ectopic beats, peripheral vascular disease, poor skin contact and limited battery life 23.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of a smartwatch based single-lead electrocardiogram device in detection of atrial fibrillation

Rajakariar

Koshy

Sajeev

et al. 2020

Heart

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ObjectiveThe AliveCor KardiaBand (KB) is an Food and Drug Administration-approved smartwatch-based cardiac rhythm monitor that records a lead-Intelligent ECG (iECG). Despite the appeal of wearable integrated ECG devices, there is a paucity of data evaluating their accuracy in diagnosing atrial fibrillation (AF). We evaluated whether a smartwatch-based device for AF detection is an accurate tool for diagnosing AF when compared with 12-lead ECG.MethodsA prospective, multi-centre, validation study was conducted in an inpatient hospital setting. The KB paired with a smartwatch, generated an automated diagnosis of AF or sinus rhythm (SR). This was compared with a 12-lead ECG performed immediately after iECG tracing. Where an unclassified or no-analysis tracing was generated, repeat iECG was performed.Results439 ECGs (iECGs (n=239) and 12-lead ECG (n=200)) were recorded in 200 patients (AF: n=38; SR: n=162) from three tertiary centres. Sensitivity and specificity using KB was 94.4% and 81.9% respectively, with a positive predictive value of 54.8% and negative predictive value of 98.4%. Agreement between 12-lead ECG and KB diagnosis was moderate when unclassified tracings were included (κ=0.60, 95% CI 0.47 to 0.72). Combining the automated device diagnosis with blinded electrophysiologists (EP) interpretation of unclassified tracings improved overall agreement (EP1: κ=0.76, 95% CI 0.65 to 0.87; EP2: κ=0.74, 95% CI 0.63 to 0.86).ConclusionThe KB demonstrated moderate diagnostic accuracy when compared with a 12-lead ECG. Combining the automated device diagnosis with EP interpretation of unclassified tracings yielded improved accuracy. However, even with future improvements in automated algorithms, physician involvement will likely remain an essential component when exploring the utility of these devices for arrhythmia screening.Clinical trial registrationURL: https://www.anzctr.org.au/ Unique identifier: ACTRN12616001374459.

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Section: Discussionmentioning

confidence: 99%

Accuracy of a smartwatch based single-lead electrocardiogram device in detection of atrial fibrillation

Rajakariar

Koshy

Sajeev

et al. 2020

Heart

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“…This problem is familiar to those in IoT where regional application of technology in rural settings even within developed countries have unreliable connectivity. Nonetheless, demonstrations of current capabilities exist: US FDA approved heart ECG monitors that function well, including across ocean distances over time, are commercially available [155].…”

Section: Network Diagnostics Of Diseases and Real-time Bioinformatics Capabilitiesmentioning

confidence: 99%

A Cross-Disciplinary View of Testing and Bioinformatic Analysis of SARS-CoV-2 and Other Human Respiratory Viruses in Pandemic Settings

Hossain¹,

Brito-Rodriguez

Sedger

et al. 2021

IEEE Access

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The SARS-Coronavirus-2 (SARS-CoV-2) infectious disease, COVID-19, has spread rapidly, resulting in a global pandemic with significant mortality. The combination of early diagnosis via rapid screening, contact tracing, social distancing and quarantine has helped to control the pandemic. The absence of real time response and diagnosis is a crucial technology shortfall and is a key reason why current contact tracing methods are inadequate to control spread. In contrast, current information technology combined with a new generation of near-real time tests offers consumer-engaged smartphone-based "lab-in-a-phone" internet-of-things (IoT) connected devices that provide increased pandemic monitoring. This review brings together key aspects required to create an entire global diagnostic ecosystem. Cross-disciplinary understanding and integration of both mechanisms and technologies for effective detection, incidence mapping and disease containment in near real-time is summarized. Available measures to monitor and/or sterilize surfaces, next-generation laboratory and smartphone-based diagnostic approaches can be brought together and networked for instant global monitoring that informs Public Health policy. Cloud-based analysis enabling real-time mapping will enable future pandemic control, drive the suppression and elimination of disease spread, saving millions of lives globally. A new paradigm is introducedscaled and multiple diagnostics for mapping and spreading of a pandemic rather than traditional accumulation of individual measurements. This can do away with the need for ultra-precise and ultra-accurate analysis by taking mass measurements that can relax tolerances and build resilience through networked analytics and informatics, the basis for novel swarm diagnostics. These include addressing ethical standards, local, national and international collaborative engagement, multidisciplinary and analytical measurements and standards, and data handling and storage protocols.

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“…Nonetheless, within certain domains demonstrations of this capability are becoming evident. For example, in the US FDA approved heart ECG monitors exist and function well with long-distance patient data studies over time [67]. A broader global effort for use of such technology is being undermined by a growing global divide concerned with ethics and where some societies are attempting to establish separate controlled internets, an approach that has probably contributed to the persistent culture of unsatisfactory information disclosure during the current and recent pandemics.…”

Section: Smartphone Based Rapid Diagnosticsmentioning

confidence: 99%

Network Diagnostics for Rapid Testing, Mapping and Bioinformatics Analysis of SARS-CoV-2 and Other Human Respiratory Viruses in Pandemic Settings

Hossain¹

2021

Preprint

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Rise of the smart device ECG and what it means for the general cardiologist

Cited by 8 publications

References 3 publications

Accuracy of a smartwatch based single-lead electrocardiogram device in detection of atrial fibrillation

Accuracy of a smartwatch based single-lead electrocardiogram device in detection of atrial fibrillation

A Cross-Disciplinary View of Testing and Bioinformatic Analysis of SARS-CoV-2 and Other Human Respiratory Viruses in Pandemic Settings

Network Diagnostics for Rapid Testing, Mapping and Bioinformatics Analysis of SARS-CoV-2 and Other Human Respiratory Viruses in Pandemic Settings

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