Accuracy of a Standalone Atrial Fibrillation Detection Algorithm Added to a Popular Wristband and Smartwatch: Prospective Diagnostic Accuracy Study.

BACKGROUND: Silent paroxysmal atrial fibrillation (AF) may be difficult to diagnose, and AF burden is hard to establish. In contrast to conventional diagnostic devices, photoplethysmography (PPG)-driven smartwatches or wristbands allow for long-term continuous heart rhythm assessment. However, most smartwatches lack an integrated PPG-AF algorithm. Adding a standalone PPG-AF algorithm to these wrist devices might open new possibilities for AF screening and burden assessment. OBJECTIVE: The aim of this study was to assess the accuracy of a well-known standalone PPG-AF detection algorithm added to a popular wristband and smartwatch, with regard to discriminating AF and sinus rhythm, in a group of patients with AF before and after cardioversion (CV). METHODS: Consecutive consenting patients with AF admitted for CV in a large academic hospital in Amsterdam, the Netherlands, were asked to wear a Biostrap wristband or Fitbit Ionic smartwatch with Fibricheck algorithm add-on surrounding the procedure. A set of 1-min PPG measurements and 12-lead reference electrocardiograms was obtained before and after CV. Rhythm assessment by the PPG device-software combination was compared with the 12-lead electrocardiogram. RESULTS: A total of 78 patients were included in the Biostrap-Fibricheck cohort (156 measurement sets) and 73 patients in the Fitbit-Fibricheck cohort (143 measurement sets). Of the measurement sets, 19/156 (12%) and 7/143 (5%), respectively, were not classifiable by the PPG algorithm due to bad quality. The diagnostic performance in terms of sensitivity, specificity, positive predictive value, negative predictive value, and accuracy was 98%, 96%, 96%, 99%, 97%, and 97%, 100%, 100%, 97%, and 99%, respectively, at an AF prevalence of ~50%. CONCLUSIONS: This study demonstrates that the addition of a well-known standalone PPG-AF detection algorithm to a popular PPG smartwatch and wristband without integrated algorithm yields a high accuracy for the detection of AF, with an acceptable unclassifiable rate, in a semicontrolled environment.

Two cases of COVID-19 monitored by a wearable biosensor-a case report.

Wearable devices have gained popularity in recent years for tracking metrics related to personal health and well-being such as vital signs, motion, and sleep. Wearable devices are considered to have a very high potential value for detecting, monitoring, and controlling the spread of infectious diseases such as COVID-19, based on their ability to collect data in a non-invasive and contactless manner. With the Biostrap wrist-worn device (Biostrap USA LLC, Duarte, CA, USA), a commercially available, clinically validated wearable device that uses photoplethysmography to automatically record physiological data such as resting heart rate, respiratory rate, oxygen saturation (SpO2), and arterial stiffness (AS), we collected biometric data from 933 subjects. We present two cases of patients who have tested positive for the presence of severe acute respiratory syndrome (SARS-CoV-2), a 24-year-old man experiencing major symptoms and another a 49-year-old man with only intermittent fatigue, and show the marked changes in biometric measurements around dates of symptom onset and positive test. We observed a pattern of sustained respiratory rate elevation in both patients, punctuated by a sharp spike in heart rate and decreased AS. The latter contradicted our expectation that during the onset of symptoms of COVID-19, an increase in AS might occur.

Mobile phones in cryptogenic strOke patients Bringing sIngle Lead ECGs for Atrial Fibrillation detection (MOBILE-AF): study protocol for a randomised controlled trial.

BACKGROUND: Recently published randomised clinical trials indicate that prolonged electrocardiom (ECG) monitoring might enhance the detection of paroxysmal atrial fibrillation (AF) in cryptogenic stroke or transient ischaemic attack (TIA) patients. A device that might be suitable for prolonged ECG monitoring is a smartphone-compatible ECG device (Kardia Mobile, Alivecor, San Francisco, CA, USA) that allows the patient to record a single-lead ECG without the presence of trained health care staff. The MOBILE-AF trial will investigate the effectiveness of the ECG device for AF detection in patients with cryptogenic stroke or TIA. In this paper, the rationale and design of the MOBILE-AF trial is presented. METHODS: For this international, multicentre trial, 200 patients with cryptogenic stroke or TIA will be randomised. One hundred patients will receive the ECG device and will be asked to record their ECG twice daily during a period of 1 year. One hundred patients will receive a 7-day Holter monitor. DISCUSSION: The primary outcome of this study is the percentage of patients in which AF is detected in the first year after the index ischaemic stroke or TIA. Secondary outcomes include markers for AF prediction, orally administered anticoagulation therapy changes, as well as the incidence of recurrent stroke and major bleeds. First results can be expected in mid-2019. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT02507986 . Registered on 15 July 2015.