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Strik M, Ploux S, van der Zande J, Velraeds A, Fontagne L, Haïssaguerre M, Bordachar P. The Use of Electrocardiogram Smartwatches in Patients with Cardiac Implantable Electrical Devices. SENSORS (BASEL, SWITZERLAND) 2024; 24:527. [PMID: 38257619 PMCID: PMC10818505 DOI: 10.3390/s24020527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/02/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024]
Abstract
Unlimited access to ECGs using an over-the-counter smartwatch constitutes a real revolution for our discipline, and the application is rapidly expanding to include patients with cardiac implantable electronic devices (CIEDs) such as pacemakers (PMs) and implantable cardioverter defibrillators (ICDs). CIEDs require periodic evaluation and adjustment by healthcare professionals. In addition, implanted patients often present with symptoms that may be related to their PMs or ICDs. An ECG smartwatch could reveal information about device functioning, confirm normal device function, or aid in the case of device troubleshooting. In this review, we delve into the available evidence surrounding smartwatches with ECG registration and their integration into the care of patients with implanted pacemakers and ICDs. We explore safety considerations and the benefits and limitations associated with these wearables, drawing on relevant studies and case series from our own experience. By analyzing the current landscape of this emerging technology, we aim to provide a comprehensive overview that facilitates informed decision-making for both healthcare professionals and patients.
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Affiliation(s)
- Marc Strik
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac-Bordeaux, France; (S.P.); (M.H.); (P.B.)
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
| | - Sylvain Ploux
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac-Bordeaux, France; (S.P.); (M.H.); (P.B.)
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
| | - Joske van der Zande
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
- Cardiovascular and Respiratory Physiology, Twente University, 7522 NB Enschede, The Netherlands
| | - Anouk Velraeds
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
- Cardiovascular and Respiratory Physiology, Twente University, 7522 NB Enschede, The Netherlands
| | - Leslie Fontagne
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac-Bordeaux, France; (S.P.); (M.H.); (P.B.)
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
| | - Michel Haïssaguerre
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac-Bordeaux, France; (S.P.); (M.H.); (P.B.)
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
| | - Pierre Bordachar
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac-Bordeaux, France; (S.P.); (M.H.); (P.B.)
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; (J.v.d.Z.); (A.V.)
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Shrestha AB, Khanal B, Mainali N, Shrestha S, Chapagain S, Umar TP, Jaiswal V. Navigating the Role of Smartwatches in Cardiac Fitness Monitoring: Insights From Physicians and the Evolving Landscape. Curr Probl Cardiol 2024; 49:102073. [PMID: 37689377 DOI: 10.1016/j.cpcardiol.2023.102073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 08/31/2023] [Accepted: 09/04/2023] [Indexed: 09/11/2023]
Abstract
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.
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Affiliation(s)
| | | | - Nischal Mainali
- Kathmandu Medical College and Teaching Hospital, Sinamangal, Kathmandu, Nepal
| | | | - Sanskriti Chapagain
- Devdaha Medical College and Research Institiute Pvt. Ltd, Devdaha, Rupandehi, Nepal
| | - Tungki Pratama Umar
- UCL Centre for Nanotechnology and Regenerative Medicine, Division of Surgery and Interventional Science, University College London, London, UK
| | - Vikash Jaiswal
- Department of Research and Academic Affairs, Larkin Community Hospital, South Miami, FL
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Dechert BE, LaPage MJ. When Do Smartwatch Heart Rate Concerns in Children Indicate Arrhythmia? J Pediatr 2023; 263:113717. [PMID: 37660972 DOI: 10.1016/j.jpeds.2023.113717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/23/2023] [Accepted: 08/29/2023] [Indexed: 09/05/2023]
Abstract
OBJECTIVE To determine the incidence and predictors of true arrhythmia in pediatric patients presenting with concerns about smartwatch cardiac data. STUDY DESIGN Single-center, retrospective cohort study of children aged 10-18 years who had presented to a pediatric cardiology clinic between January 2018 and December 2021 with concerns related to smartwatch cardiac data. The primary study outcome was diagnosis of arrhythmia based on clinical evaluation or documentation of arrhythmia by clinical testing. RESULTS There were 126 patients (mean age 15.6 ± 2.4 years) who presented with a smartwatch-based rhythm concern, with tachycardia in 89%. In all, 19 of 126 (15%) patients were diagnosed with true arrhythmia. The odds of a true arrhythmia diagnosis with symptoms vs no symptoms were 3.2 (95% CI 0.7-14.5), and with heart rate (HR) ≥190 beats/min vs HR <190 beats/min, it was 14.3 (95% CI 3.8-52.8). The positive predictive value of HR ≥190 beats/min and symptoms together to predict arrhythmia was only 39% (95% CI 28-52). The negative predictive value for arrhythmia having neither symptoms nor HR >190 was 95% (95% CI 75-99). CONCLUSION The likelihood of a true arrhythmia in pediatric patients presenting with a smartwatch-based HR concern was low. Rarely, smartwatch electrograms or trend data were sufficient for arrhythmia diagnosis.
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Affiliation(s)
- Brynn E Dechert
- Department of Pediatrics, University of Michigan, Ann Arbor, MI.
| | - Martin J LaPage
- Department of Pediatrics, University of Michigan, Ann Arbor, MI
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Bin KJ, De Pretto LR, Sanchez FB, De Souza E Castro FPM, Ramos VD, Battistella LR. Digital Platform for Continuous Monitoring of Patients Using a Smartwatch: Longitudinal Prospective Cohort Study. JMIR Form Res 2023; 7:e47388. [PMID: 37698916 PMCID: PMC10523215 DOI: 10.2196/47388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND Since the COVID-19 pandemic, there has been a boost in the digital transformation of the human society, where wearable devices such as a smartwatch can already measure vital signs in a continuous and naturalistic way; however, the security and privacy of personal data is a challenge to expanding the use of these data by health professionals in clinical follow-up for decision-making. Similar to the European General Data Protection Regulation, in Brazil, the Lei Geral de Proteção de Dados established rules and guidelines for the processing of personal data, including those used for patient care, such as those captured by smartwatches. Thus, in any telemonitoring scenario, there is a need to comply with rules and regulations, making this issue a challenge to overcome. OBJECTIVE This study aimed to build a digital solution model for capturing data from wearable devices and making them available in a safe and agile manner for clinical and research use, following current laws. METHODS A functional model was built following the Brazilian Lei Geral de Proteção de Dados (2018), where data captured by smartwatches can be transmitted anonymously over the Internet of Things and be identified later within the hospital. A total of 80 volunteers were selected for a 24-week follow-up clinical trial divided into 2 groups, one group with a previous diagnosis of COVID-19 and a control group without a previous diagnosis of COVID-19, to measure the synchronization rate of the platform with the devices and the accuracy and precision of the smartwatch in out-of-hospital conditions to simulate remote monitoring at home. RESULTS In a 35-week clinical trial, >11.2 million records were collected with no system downtime; 66% of continuous beats per minute were synchronized within 24 hours (79% within 2 days and 91% within a week). In the limit of agreement analysis, the mean differences in oxygen saturation, diastolic blood pressure, systolic blood pressure, and heart rate were -1.280% (SD 5.679%), -1.399 (SD 19.112) mm Hg, -1.536 (SD 24.244) mm Hg, and 0.566 (SD 3.114) beats per minute, respectively. Furthermore, there was no difference in the 2 study groups in terms of data analysis (neither using the smartwatch nor the gold-standard devices), but it is worth mentioning that all volunteers in the COVID-19 group were already cured of the infection and were highly functional in their daily work life. CONCLUSIONS On the basis of the results obtained, considering the validation conditions of accuracy and precision and simulating an extrahospital use environment, the functional model built in this study is capable of capturing data from the smartwatch and anonymously providing it to health care services, where they can be treated according to the legislation and be used to support clinical decisions during remote monitoring.
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Affiliation(s)
- Kaio Jia Bin
- Instituto de Medicina Física e Reabilitação, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Lucas Ramos De Pretto
- Instituto de Medicina Física e Reabilitação, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Fábio Beltrame Sanchez
- Instituto de Medicina Física e Reabilitação, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | | | - Vinicius Delgado Ramos
- Instituto de Medicina Física e Reabilitação, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Linamara Rizzo Battistella
- Instituto de Medicina Física e Reabilitação, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
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Weidlich S, Mannhart D, Serban T, Krisai P, Knecht S, Du Fay de Lavallaz J, Müller T, Schaer B, Osswald S, Kühne M, Sticherling C, Badertscher P. Accuracy in detecting atrial fibrillation in single-lead ECGs: an online survey comparing the influence of clinical expertise and smart devices. Swiss Med Wkly 2023; 153:40096. [PMID: 37769610 DOI: 10.57187/smw.2023.40096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023] Open
Abstract
BACKGROUND Manual interpretation of single-lead ECGs (SL-ECGs) is often required to confirm a diagnosis of atrial fibrillation. However accuracy in detecting atrial fibrillation via SL-ECGs may vary according to clinical expertise and choice of smart device. AIMS To compare the accuracy of cardiologists, internal medicine residents and medical students in detecting atrial fibrillation via SL-ECGs from five different smart devices (Apple Watch, Fitbit Sense, KardiaMobile, Samsung Galaxy Watch, Withings ScanWatch). Participants were also asked to assess the quality and readability of SL-ECGs. METHODS In this prospective study (BaselWearableStudy, NCT04809922), electronic invitations to participate in an online survey were sent to physicians at major Swiss hospitals and to medical students at Swiss universities. Participants were asked to classify up to 50 SL-ECGs (from ten patients and five devices) into three categories: sinus rhythm, atrial fibrillation or inconclusive. This classification was compared to the diagnosis via a near-simultaneous 12-lead ECG recording interpreted by two independent cardiologists. In addition, participants were asked their preference of each manufacturer's SL-ECG. RESULTS Overall, 450 participants interpreted 10,865 SL-ECGs. Sensitivity and specificity for the detection of atrial fibrillation via SL-ECG were 72% and 92% for cardiologists, 68% and 86% for internal medicine residents, 54% and 65% for medical students in year 4-6 and 44% and 58% for medical students in year 1-3; p <0.001. Participants who stated prior experience in interpreting SL-ECGs demonstrated a sensitivity and specificity of 63% and 81% compared to a sensitivity and specificity of 54% and 67% for participants with no prior experience in interpreting SL-ECGs (p <0.001). Of all participants, 107 interpreted all 50 SL-ECGs. Diagnostic accuracy for the first five interpreted SL-ECGs was 60% (IQR 40-80%) and diagnostic accuracy for the last five interpreted SL-ECGs was 80% (IQR 60-90%); p <0.001. No significant difference in the accuracy of atrial fibrillation detection was seen between the five smart devices; p = 0.33. SL-ECGs from the Apple Watch were considered as having the best quality and readability by 203 (45%) and 226 (50%) participants, respectively. CONCLUSION SL-ECGs can be challenging to interpret. Accuracy in correctly identifying atrial fibrillation depends on clinical expertise, while the choice of smart device seems to have no impact.
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Affiliation(s)
- Simon Weidlich
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Diego Mannhart
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Teodor Serban
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Philipp Krisai
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Sven Knecht
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Jeanne Du Fay de Lavallaz
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Tatjana Müller
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Beat Schaer
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Stefan Osswald
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Michael Kühne
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Christian Sticherling
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Patrick Badertscher
- Department of Cardiology, University Hospital Basel, Basel, Switzerland
- Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
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Knecht S, Waldmann F, Kuhn R, Mannhart D, Kühne M, Sticherling C, Badertscher P, Wildhaber RA. Technical Characterization of Single-Lead ECG Signals From 4 Different Smartwatches and its Potential Clinical Implications. JACC Clin Electrophysiol 2023; 9:1415-1417. [PMID: 37074248 DOI: 10.1016/j.jacep.2023.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/06/2023] [Accepted: 03/15/2023] [Indexed: 04/20/2023]
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Yee-ming Li J, Kwok SY, Tsao S, Hoi-yan Chung C, Hing-sang Wong W, Cheung YF. Detection of QT interval prolongation using Apple Watch electrocardiogram in children and adolescents with congenital long QT syndrome. IJC HEART & VASCULATURE 2023; 47:101232. [PMID: 37346232 PMCID: PMC10279543 DOI: 10.1016/j.ijcha.2023.101232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/22/2023] [Accepted: 06/05/2023] [Indexed: 06/23/2023]
Abstract
Background Apple watch-derived electrocardiogram (awECG) may help identify prolongation of corrected QT (QTc) interval. This study aimed to determine its usefulness for assessment of prolongation of QTc interval in children and adolescents with long QT syndrome (LQTS). Methods Children and adolescents with and without LQTS were recruited for measurement of QTc intervals based on standard 12-lead (sECG) and awECG lead I, II and V5 tracings. Bland-Altman analysis of reproducibility, concordance assessment of T wave morphologies, and receiver operating characteristic (ROC) analysis of sensitivity and specificity of awECG-derived QTc interval for detecting QTc prolongation were performed. Results Forty-nine patients, 19 with and 30 without LQTS, aged 3-22 years were studied. The intraclass correlation coefficient was 1.00 for both intra- and inter-observer variability in the measurement of QTc interval. The awECG- and sECG-derived QTc intervals correlated strongly in all three leads (r = 0.90-0.93, all p < 0.001). Concordance between awECG and sECG in assessing T wave morphologies was 84% (16/19). For detection of QTc prolongation, awECG lead V5 had the best specificity (94.4% and 87.5%, respectively) and positive predictive value (87.5% and 80.0%, respectively), and for identification of patients with LQTS, awECG leads II and V5 had the greatest specificity (92.3%-94.1%) and positive predictive value (85.7% to 91.7%) in both males and females. Conclusions Apple Watch leads II and V5 tracings can be used for reproducible and accurate measurement of QTc interval, ascertainment of abnormal T wave morphologies, and detection of prolonged QTc interval in children and adolescents with LQTS.
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Affiliation(s)
- Jennifer Yee-ming Li
- Department of Paediatrics and Adolescent Medicine, Hong Kong Children’s Hospital, Hong Kong
| | - Sit-yee Kwok
- Department of Paediatrics and Adolescent Medicine, Hong Kong Children’s Hospital, Hong Kong
| | - Sabrina Tsao
- Department of Paediatrics and Adolescent Medicine, Hong Kong Children’s Hospital, Hong Kong
- Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Charis Hoi-yan Chung
- Department of Paediatrics and Adolescent Medicine, Hong Kong Children’s Hospital, Hong Kong
| | - Wilfred Hing-sang Wong
- Department of Paediatrics and Adolescent Medicine, Hong Kong Children’s Hospital, Hong Kong
| | - Yiu-fai Cheung
- Department of Paediatrics and Adolescent Medicine, Hong Kong Children’s Hospital, Hong Kong
- Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
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Zepeda-Echavarria A, van de Leur RR, van Sleuwen M, Hassink RJ, Wildbergh TX, Doevendans PA, Jaspers J, van Es R. Electrocardiogram Devices for Home Use: Technological and Clinical Scoping Review. JMIR Cardio 2023; 7:e44003. [PMID: 37418308 PMCID: PMC10362423 DOI: 10.2196/44003] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/29/2023] [Accepted: 06/06/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND Electrocardiograms (ECGs) are used by physicians to record, monitor, and diagnose the electrical activity of the heart. Recent technological advances have allowed ECG devices to move out of the clinic and into the home environment. There is a great variety of mobile ECG devices with the capabilities to be used in home environments. OBJECTIVE This scoping review aimed to provide a comprehensive overview of the current landscape of mobile ECG devices, including the technology used, intended clinical use, and available clinical evidence. METHODS We conducted a scoping review to identify studies concerning mobile ECG devices in the electronic database PubMed. Secondarily, an internet search was performed to identify other ECG devices available in the market. We summarized the devices' technical information and usability characteristics based on manufacturer data such as datasheets and user manuals. For each device, we searched for clinical evidence on the capabilities to record heart disorders by performing individual searches in PubMed and ClinicalTrials.gov, as well as the Food and Drug Administration (FDA) 510(k) Premarket Notification and De Novo databases. RESULTS From the PubMed database and internet search, we identified 58 ECG devices with available manufacturer information. Technical characteristics such as shape, number of electrodes, and signal processing influence the capabilities of the devices to record cardiac disorders. Of the 58 devices, only 26 (45%) had clinical evidence available regarding their ability to detect heart disorders such as rhythm disorders, more specifically atrial fibrillation. CONCLUSIONS ECG devices available in the market are mainly intended to be used for the detection of arrhythmias. No devices are intended to be used for the detection of other cardiac disorders. Technical and design characteristics influence the intended use of the devices and use environments. For mobile ECG devices to be intended to detect other cardiac disorders, challenges regarding signal processing and sensor characteristics should be solved to increase their detection capabilities. Devices recently released include the use of other sensors on ECG devices to increase their detection capabilities.
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Affiliation(s)
- Alejandra Zepeda-Echavarria
- Medical Technologies and Clinical Physics, Facilitation Department, University Medical Center Utrecht, Utrecht, Netherlands
| | - Rutger R van de Leur
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | - Meike van Sleuwen
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | - Rutger J Hassink
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Pieter A Doevendans
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
- HeartEye BV, Delft, Netherlands
- Netherlands Heart Institute, Utrecht, Netherlands
| | - Joris Jaspers
- Medical Technologies and Clinical Physics, Facilitation Department, University Medical Center Utrecht, Utrecht, Netherlands
| | - René van Es
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
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van der Zande J, Strik M, Dubois R, Ploux S, Alrub SA, Caillol T, Nasarre M, Donker DW, Oppersma E, Bordachar P. Using a Smartwatch to Record Precordial Electrocardiograms: A Validation Study. SENSORS (BASEL, SWITZERLAND) 2023; 23:2555. [PMID: 36904759 PMCID: PMC10007514 DOI: 10.3390/s23052555] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
Smartwatches that support the recording of a single-lead electrocardiogram (ECG) are increasingly being used beyond the wrist, by placement on the ankle and on the chest. However, the reliability of frontal and precordial ECGs other than lead I is unknown. This clinical validation study assessed the reliability of an Apple Watch (AW) to obtain conventional frontal and precordial leads as compared to standard 12-lead ECGs in both subjects without known cardiac anomalies and patients with underlying heart disease. In 200 subjects (67% with ECG anomalies), a standard 12-lead ECG was performed, followed by AW recordings of the standard Einthoven leads (leads I, II, and III) and precordial leads V1, V3, and V6. Seven parameters (P, QRS, ST, and T-wave amplitudes, PR, QRS, and QT intervals) were compared through a Bland-Altman analysis, including the bias, absolute offset, and 95% limits of agreement. AW-ECGs recorded on the wrist but also beyond the wrist had similar durations and amplitudes compared to standard 12-lead ECGs. Significantly greater amplitudes were measured by the AW for R-waves in precordial leads V1, V3, and V6 (+0.094 mV, +0.149 mV, +0.129 mV, respectively, all p < 0.001), indicating a positive bias for the AW. AW can be used to record frontal, and precordial ECG leads, paving the way for broader clinical applications.
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Affiliation(s)
- Joske van der Zande
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac, France
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
- Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Marc Strik
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac, France
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
| | - Rémi Dubois
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac, France
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
| | - Sylvain Ploux
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac, France
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
| | - Saer Abu Alrub
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
- Cardiology Department, Clermont Universite, Université d’Auvergne, Cardio Vascular Interventional Therapy and Imaging (CaVITI), Image Science for Interventional Techniques (ISIT), UMR6284, CHU Clermont-Ferrand, F-63003 Clermont-Ferrand, France
| | - Théo Caillol
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac, France
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
| | - Mathieu Nasarre
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
| | - Dirk W. Donker
- Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Eline Oppersma
- Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands
| | - Pierre Bordachar
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac, France
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), F-33600 Pessac, France
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Kota VD, Sharma H, Albert MV, Mahbub I, Mehta G, Namuduri K. A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson. SENSORS (BASEL, SWITZERLAND) 2023; 23:2270. [PMID: 36850868 PMCID: PMC9959289 DOI: 10.3390/s23042270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
The survival rate for sudden cardiac arrest (SCA) is low, and patients with long-term risks of SCA are not adequately alerted. Understanding SCA's characteristics will be key to developing preventive strategies. Many lives could be saved if SCA's early onset could be detected or predicted. Monitoring heart signals continuously is essential for diagnosing sporadic cardiac dysfunction. An electrocardiogram (ECG) can be used to continuously monitor heart function without having to go to the hospital. A zeolite-based dry electrode can provide safe on-skin ECG acquisition while the subject is out-of-hospital and facilitate long-term monitoring. To the ECG signal, a low-power 1 μW read-out circuit was designed and implemented in our prior work. However, having long-term ECG monitoring outside the hospital, i.e., high battery life, and low power consumption while transmission and reception of ECG signal are crucial. This paper proposes a prototype with a 10-bit resolution ADC and nRF24L01 transceivers placed 5 m apart. The system uses the 2.4 GHz worldwide ISM frequency band with GFSK modulation to wirelessly transmit digitized ECG bits at 250 kbps data rate to a physician's computer (or similar) for continuous monitoring of ECG signals; the power consumption is only 11.2 mW and 4.62 mW during transmission and reception, respectively, with a low bit error rate of ≤0.1%. Additionally, a subject-wise cross-validated, three-fold, optimized convolutional neural network (CNN) model using the Physionet-SCA dataset was implemented on NVIDIA Jetson to identify the irregular heartbeats yielding an accuracy of 89% with a run time of 5.31 s. Normal beat classification has an F1 score of 0.94 and a ROC score of 0.886. Thus, this paper integrates the ECG acquisition and processing unit with low-power wireless transmission and CNN model to detect irregular heartbeats.
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Affiliation(s)
- Venkata Deepa Kota
- Department of Electrical Engineering, University of North Texas, Denton, TX 76203, USA
| | - Himanshu Sharma
- Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, USA
| | - Mark V. Albert
- Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, USA
| | - Ifana Mahbub
- Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
| | - Gayatri Mehta
- Department of Electrical Engineering, University of North Texas, Denton, TX 76203, USA
| | - Kamesh Namuduri
- Department of Electrical Engineering, University of North Texas, Denton, TX 76203, USA
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11
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Galgut O, Le Page P, Mitchell ARJ. Watch for tachycardia. INTERNATIONAL JOURNAL OF ARRHYTHMIA 2022. [DOI: 10.1186/s42444-022-00081-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Background
Wearable devices capable of measuring health metrics are becoming increasingly prevalent. Most work has investigated the potential for these devices in the context of atrial fibrillation, our case highlights the potential of wearable devices across a wider range of arrhythmia.
Case presentation
A 51-year-old woman was referred to the cardiology clinic for an assessment of symptoms of intermittent exertional shortness of breath and palpitation. The patient was otherwise fit and well, took limited alcohol and no caffeine, and was a never smoker. There was no family history of heart disease. Physical examination in clinic was unremarkable, and a 12-lead electrocardiogram (ECG), seven-day ambulatory ECG, exercise stress ECG, and trans-thoracic echocardiogram were all normal. During a severe episode the patient recorded an ECG using an Apple Watch (Apple Inc, California, USA). This was forwarded to the patient’s cardiologist, who suspected a broad complex tachycardia and organised an urgent follow-up appointment. A further 72-h Holter ECG monitor showed frequent sustained periods of monomorphic ventricular tachycardia, confirming the watch findings. The patient was started on beta blocker therapy with a rapid improvement in symptoms.
Conclusions
Current smartwatch technology can reliably identify irregular rhythms and can distinguish atrial fibrillation from sinus rhythm, with emerging evidence supporting detection of other cardiovascular diseases, including medical emergencies. There may also be a role for wearable devices in screening young populations for predictors of sudden cardiac death. At present device outputs require clinician interpretation, but in the future patients may present to primary or secondary care with a firm diagnosis of arrhythmia and may already be making wearable device guided behaviour changes.
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12
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Racine HP, Strik M, van der Zande J, Alrub SA, Caillol T, Haïssaguerre M, Ploux S, Bordachar P. Role of Coexisting ECG Anomalies in the Accuracy of Smartwatch ECG Detection of Atrial Fibrillation. Can J Cardiol 2022; 38:1709-1712. [PMID: 36334937 DOI: 10.1016/j.cjca.2022.08.222] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/02/2022] [Accepted: 08/14/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Hugo-Pierre Racine
- Institut Universitaire de Cardiologie et de Pneumologie de Québec, Université Laval, Québec, Québec, Canada; Cardiothoracic Unit, Bordeaux University Hospital, Pessac, France
| | - Marc Strik
- Cardiothoracic Unit, Bordeaux University Hospital, Pessac, France; IHU Liryc, Electrophysiology and Heart Modelling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.
| | - Joske van der Zande
- IHU Liryc, Electrophysiology and Heart Modelling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France; Twente University, Twente, The Netherlands
| | - Saer Abu Alrub
- Cardiology Department, CHU Clermont-Ferrand, Clermont-Ferrand, France
| | - Théo Caillol
- Cardiothoracic Unit, Bordeaux University Hospital, Pessac, France
| | - Michel Haïssaguerre
- Cardiothoracic Unit, Bordeaux University Hospital, Pessac, France; IHU Liryc, Electrophysiology and Heart Modelling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Sylvain Ploux
- Cardiothoracic Unit, Bordeaux University Hospital, Pessac, France; IHU Liryc, Electrophysiology and Heart Modelling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
| | - Pierre Bordachar
- Cardiothoracic Unit, Bordeaux University Hospital, Pessac, France; IHU Liryc, Electrophysiology and Heart Modelling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France
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13
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Bin KJ, De Pretto LR, Sanchez FB, Battistella LR. Digital Platform to Continuously Monitor Patients Using a Smartwatch: Preliminary Report. JMIR Form Res 2022; 6:e40468. [PMID: 36107471 PMCID: PMC9523529 DOI: 10.2196/40468] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 08/01/2022] [Accepted: 08/23/2022] [Indexed: 11/28/2022] Open
Abstract
Background Monitoring vital signs such as oximetry, blood pressure, and heart rate is important to follow the evolution of patients. Smartwatches are a revolution in medicine allowing the collection of such data in a continuous and organic way. However, it is still a challenge to make this information available to health care professionals to make decisions during clinical follow-up. Objective This study aims to build a digital solution that displays vital sign data from smartwatches, collected remotely, continuously, reliably, and from multiple users, with trigger warnings when abnormal results are identified. Methods This is a single-center prospective study following the guidelines “Evaluating digital health products” from the UK Health Security Agency. A digital platform with 3 different applications was created to capture and display data from the mobile phones of volunteers with smartwatches. We selected 80 volunteers who were followed for 24 weeks each, and the synchronization interval between the smartwatch and digital solution was recorded for each vital sign collected. Results In 14 weeks of project progress, we managed to recruit 80 volunteers, with 68 already registered in the digital solution. More than 2.8 million records have already been collected, without system downtime. Less than 5% of continuous heart rate measurements (bpm) were synchronized within 2 hours. However, approximately 70% were synchronized in less than 24 hours, and 90% were synchronized in less than 119 hours. Conclusions The digital solution is working properly in its role of displaying data collected from smartwatches. Vital sign values are being monitored by the research team as part of the monitoring of volunteers. Although the digital solution proved unsuitable for monitoring urgent events, it is more than suitable for use in outpatient clinical use. This digital solution, which is based on cloud technology, can be applied in the future for telemonitoring in regions lacking health care professionals. Accuracy and reliability studies still need to be performed at the end of the 24-week follow-up.
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Affiliation(s)
- Kaio Jia Bin
- Instituto de Medicina Física e Reabilitação do Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Lucas Ramos De Pretto
- Instituto de Medicina Física e Reabilitação do Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Fabio Beltrame Sanchez
- Instituto de Medicina Física e Reabilitação do Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Linamara Rizzo Battistella
- Instituto de Medicina Física e Reabilitação do Hospital das Clínicas, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
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14
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Strik M, Bordachar P. Smart interpretation of the smartwatch ECG: consider the false negatives – Authors’ reply. Europace 2022; 24:1710-1711. [DOI: 10.1093/europace/euac073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 04/27/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Marc Strik
- Bordeaux University Hospital (CHU), Cardio-Thoracic Unit , F-33600 Pessac , France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université , F-33600 Pessac- Bordeaux , France
| | - Pierre Bordachar
- Bordeaux University Hospital (CHU), Cardio-Thoracic Unit , F-33600 Pessac , France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, fondation Bordeaux Université , F-33600 Pessac- Bordeaux , France
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15
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Cheung CC, Scheinman M. A smart interpretation of the smartwatch ECG: consider the false negatives. Europace 2022; 24:1710. [PMID: 35654765 DOI: 10.1093/europace/euac070] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 04/10/2022] [Indexed: 11/14/2022] Open
Affiliation(s)
- Christopher C Cheung
- Section of Cardiac Electrophysiology, University of California San Francisco, 505 Parnassus Avenue 94143 San Francisco, USA
| | - Melvin Scheinman
- Section of Cardiac Electrophysiology, University of California San Francisco, 505 Parnassus Avenue 94143 San Francisco, USA
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16
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Machine learning-based optimization of pre-symptomatic COVID-19 detection through smartwatch. Sci Rep 2022; 12:7886. [PMID: 35550526 PMCID: PMC9097889 DOI: 10.1038/s41598-022-11329-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 04/20/2022] [Indexed: 11/22/2022] Open
Abstract
Patients with weak or no symptoms accelerate the spread of COVID-19 through various mutations and require more aggressive and active means of validating the COVID-19 infection. More than 30% of patients are reported as asymptomatic infection after the delta mutation spread in Korea. It means that there is a need for a means to more actively and accurately validate the infection of the epidemic via pre-symptomatic detection, besides confirming the infection via the symptoms. Mishara et al. (Nat Biomed Eng 4, 1208–1220, 2020) reported that physiological data collected from smartwatches could be an indicator to suspect COVID-19 infection. It shows that it is possible to identify an abnormal state suspected of COVID-19 by applying an anomaly detection method for the smartwatch’s physiological data and identifying the subject’s abnormal state to be observed. This paper proposes to apply the One Class-Support Vector Machine (OC-SVM) for pre-symptomatic COVID-19 detection. We show that OC-SVM can provide better performance than the Mahalanobis distance-based method used by Mishara et al. (Nat Biomed Eng 4, 1208–1220, 2020) in three aspects: earlier (23.5–40% earlier) and more detection (13.2–19.1% relative better) and fewer false positives. As a result, we could conclude that OC-SVM using Resting Heart Rate (RHR) with 350 and 300 moving average size is the most recommended technique for COVID-19 pre-symptomatic detection based on physiological data from the smartwatch.
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17
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Xintarakou A, Sousonis V, Asvestas D, Vardas PE, Tzeis S. Remote Cardiac Rhythm Monitoring in the Era of Smart Wearables: Present Assets and Future Perspectives. Front Cardiovasc Med 2022; 9:853614. [PMID: 35299975 PMCID: PMC8921479 DOI: 10.3389/fcvm.2022.853614] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/08/2022] [Indexed: 12/14/2022] Open
Abstract
Remote monitoring and control of heart function are of primary importance for patient evaluation and management, especially in the modern era of precision medicine and personalized approach. Breaking technological developments have brought to the frontline a variety of smart wearable devices, such as smartwatches, chest patches/straps, or sensors integrated into clothing and footwear, which allow continuous and real-time recording of heart rate, facilitating the detection of cardiac arrhythmias. However, there is great diversity and significant differences in the type and quality of the information they provide, thus impairing their integration into daily clinical practice and the relevant familiarization of practicing physicians. This review will summarize the different types and dominant functions of cardiac smart wearables available in the market. Furthermore, we report the devices certified by official American and/or European authorities and the respective sources of evidence. Finally, we comment pertinent limitations and caveats as well as the potential answers that flow from the latest technological achievements and future perspectives.
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Affiliation(s)
| | | | | | - Panos E Vardas
- Heart Sector, Hygeia Hospitals Group, HHG, Athens, Greece.,European Heart Agency, European Society of Cardiology, Brussels, Belgium
| | - Stylianos Tzeis
- Department of Cardiology, Hygeia Group, Mitera Hospital, Athens, Greece
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18
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Abu-Alrub S, Strik M, Ramirez FD, Moussaoui N, Racine HP, Marchand H, Buliard S, Haïssaguerre M, Ploux S, Bordachar P. Smartwatch Electrocardiograms for Automated and Manual Diagnosis of Atrial Fibrillation: A Comparative Analysis of Three Models. Front Cardiovasc Med 2022; 9:836375. [PMID: 35187135 PMCID: PMC8854369 DOI: 10.3389/fcvm.2022.836375] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 01/07/2022] [Indexed: 01/05/2023] Open
Abstract
AimsThe diagnostic accuracy of proprietary smartwatch algorithms and the interpretability of smartwatch ECG tracings may differ between available models. We compared the diagnostic potential for detecting atrial fibrillation (AF) of three commercially available smartwatches.MethodsWe performed a prospective, non-randomized, and adjudicator-blinded clinical study of 100 patients in AF and 100 patients in sinus rhythm, patients with atrial flutter were excluded. All patients underwent 4 ECG recordings: a conventional 12-lead ECG, Apple Watch Series 5®, Samsung Galaxy Watch Active 3®, and Withings Move ECG® in random order. All smartwatch ECGs were analyzed using their respective automated proprietary software and by clinical experts who also graded the quality of the tracings.ResultsThe accuracy of automated AF diagnoses by Apple and Samsung outperformed that of Withings, which was attributable to a higher proportion of inconclusive ECGs with the latter (sensitivity/specificity: 87%/86% and 88%/81% vs. 78%/80%, respectively, p < 0.05). Expert interpretation was more accurate for Withings and Apple than for Samsung (sensitivity/specificity: 96%/86% and 94%/84% vs. 86%/76%, p < 0.05), driven by the high proportion of uninterpretable tracings with the latter (2 and 4% vs. 15%, p < 0.05).ConclusionDiagnosing AF is possible using various smartwatch models. However, the diagnostic accuracy of their automated interpretations varies between models as does the quality of ECG tracings recorded for manual interpretation.
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Affiliation(s)
- Saer Abu-Alrub
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
- Cardiology Department, CHU Clermont-Ferrand, Clermont-Ferrand, France
| | - Marc Strik
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
- *Correspondence: Marc Strik
| | - F. Daniel Ramirez
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
- Division of Cardiology, University of Ottawa Heart Institute, Ottawa, ON, Canada
| | - Nadir Moussaoui
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Hugo Pierre Racine
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Hugo Marchand
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Samuel Buliard
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Michel Haïssaguerre
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Sylvain Ploux
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
| | - Pierre Bordachar
- Cardio-Thoracic Unit, Bordeaux University Hospital (CHU), Bordeaux, France
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Bordeaux, France
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19
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Tooley JE, Turakhia MP. Is it time for a consumerized or home-based 12-lead electrocardiogram? Europace 2021; 24:357-358. [PMID: 34894220 DOI: 10.1093/europace/euab301] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- James E Tooley
- Center for Digital Health, Stanford University School of Medicine, Stanford, CA, USA.,Department of Medicine (Cardiovascular Medicine), Stanford University Medical Center, Palo Alto, CA, USA
| | - Mintu P Turakhia
- Center for Digital Health, Stanford University School of Medicine, Stanford, CA, USA.,Department of Medicine (Cardiovascular Medicine), Stanford University Medical Center, Palo Alto, CA, USA.,VA Palo Alto Health Care System, 3801 Miranda Ave - 111C, Palo Alto CA 94304, USA
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