IOT Based Cardiac Rhythm Monitoring System Using Geolocation and Automation

Background Atrial fibrillation (AF) is the most common tachyarrhythmia and associated with a risk of stroke. The detection and diagnosis of AF represent a major clinical challenge due to AF’s asymptomatic and intermittent nature. Novel consumer-grade mobile health (mHealth) products with automatic arrhythmia detection could be an option for long-term electrocardiogram (ECG)-based rhythm monitoring and AF detection. Objective We evaluated the feasibility and accuracy of a wearable automated mHealth arrhythmia monitoring system, including a consumer-grade, single-lead heart rate belt ECG device (heart belt), a mobile phone application, and a cloud service with an artificial intelligence (AI) arrhythmia detection algorithm for AF detection. The specific aim of this proof-of-concept study was to test the feasibility of the entire sequence of operations from ECG recording to AI arrhythmia analysis and ultimately to final AF detection. Methods Patients (n=159) with an AF (n=73) or sinus rhythm (n=86) were recruited from the emergency department. A single-lead heart belt ECG was recorded for 24 hours. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics and as a reference device in a user experience survey with patients over 65 years of age (high-risk group). Results The heart belt provided a high-quality ECG recording for visual interpretation resulting in 100% accuracy, sensitivity, and specificity of AF detection. The accuracy of AF detection with the automatic AI arrhythmia detection from the heart belt ECG recording was also high (97.5%), and the sensitivity and specificity were 100% and 95.4%, respectively. The correlation between the automatic estimated AF burden and the true AF burden from Holter recording was >0.99 with a mean burden error of 0.05 (SD 0.26) hours. The heart belt demonstrated good user experience and did not significantly interfere with the patient’s daily activities. The patients preferred the heart belt over Holter ECG for rhythm monitoring (85/110, 77% heart belt vs 77/109, 71% Holter, P=.049). Conclusions A consumer-grade, single-lead ECG heart belt provided good-quality ECG for rhythm diagnosis. The mHealth arrhythmia monitoring system, consisting of heart-belt ECG, a mobile phone application, and an automated AF detection achieved AF detection with high accuracy, sensitivity, and specificity. In addition, the mHealth arrhythmia monitoring system showed good user experience. Trial Registration ClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335

Download Full-text

Follow-up after surgical ablation therapy for atrial fibrillation (AF) using an implantable cardiac rhythm monitoring device (ICM)

The Thoracic and Cardiovascular Surgeon ◽

10.1055/s-0032-1332466 ◽

2013 ◽

Vol 61 (S 01) ◽

Author(s):

A Kowert ◽

C Vicol ◽

C Hagl ◽

G Juchem

Keyword(s):

Atrial Fibrillation ◽

Cardiac Rhythm ◽

Monitoring Device ◽

Surgical Ablation ◽

Ablation Therapy ◽

Rhythm Monitoring

Download Full-text

Recurrence rate of atrial fibrillation after the first clinical episode: A prospective evaluation using continuous cardiac rhythm monitoring

Clinical Cardiology ◽

10.1002/clc.22904 ◽

2018 ◽

Vol 41 (5) ◽

pp. 594-600 ◽

Cited By ~ 2

Author(s):

Emmanuel N. Simantirakis ◽

Panteleimon E. Papakonstantinou ◽

Emmanuel Kanoupakis ◽

Gregory I. Chlouverakis ◽

Stylianos Tzeis ◽

...

Keyword(s):

Atrial Fibrillation ◽

Recurrence Rate ◽

Cardiac Rhythm ◽

Prospective Evaluation ◽

Clinical Episode ◽

Rhythm Monitoring

Download Full-text

Cardiac rhythm monitoring for phenol peripheral nerve blocks in pediatric patients

Archives of Physical Medicine and Rehabilitation ◽

10.1016/0003-9993(94)90867-2 ◽

1994 ◽

Vol 75 (9) ◽

pp. 1055

Author(s):

Jean E. Shelton ◽

Bertrand A. Ross ◽

Janis E. Goodmundson ◽

Hooman Sedighi

Keyword(s):

Peripheral Nerve ◽

Cardiac Rhythm ◽

Pediatric Patients ◽

Nerve Blocks ◽

Peripheral Nerve Blocks ◽

Rhythm Monitoring

Download Full-text

Abstract 25: Paroxysmal Atrial Fibrillation is Common in Patients With Defined Etiology for Stroke: Prolonged Monitoring of Cardiac Rhythm for Detection of Atrial Fibrillation After a Cerebral Ischemic Event (PEAACE) Study

Stroke ◽

10.1161/str.45.suppl_1.25 ◽

2014 ◽

Vol 45 (suppl_1) ◽

Author(s):

Esseddeeg M Ghrooda ◽

Peter Dobrowolski ◽

Ghazala Basir ◽

Ibrahim Yaseen ◽

Nazim khan ◽

...

Keyword(s):

Atrial Fibrillation ◽

Ischemic Stroke ◽

Cardiac Rhythm ◽

Previous History ◽

Cryptogenic Stroke ◽

Predictive Score ◽

Stroke Patients ◽

Similar Frequency ◽

Stroke Team ◽

Rhythm Monitoring

Introduction: Atrial fibrillation (AF) related cardioembolic stroke accounts for over 20% of ischemic stroke. Recent reports using prolonged cardiac rhythm monitoring (PCRM) in cryptogenic stroke reveal paroxysmal AF (PAF) in an additional 20% of patients. We report our findings with PCRM in patients with and without cryptogenic stroke patients in whom an initial 24-h Holter was negative. Methods: Patients admitted to the stroke service with no previous history of AF and no AF on Holter monitoring were enrolled for 3 weeks of PCRM. We used a PAF predictive score to determine the risk of the arrhythmia. All studies were interpreted by the stroke team prior to final review by the cardiologist. Results: Between Sept 2012 and June 2013, 96 patients were evaluated. Over all PAF was diagnoses in 37.5 % of patients. PAF was diagnosed in 32% of patients with cryptogenic stroke and 36 % of patients where an additional etiology may account for the stroke diagnosis. The AF prediction score was not useful in the recognition of patients that were more likely to be at risk for AF. 96 of 98 recordings were correctly identified by the stroke team prior to final diagnosis by the cardiologist. Interpretation: PAF is more common in stroke patients than was previously suspected. It occurs with similar frequency in patients with and without cryptogenic stroke. Our data strongly supports the need for prolonged cardiac rhythm monitoring in all stroke patients to diagnose this important preventable cause of ischemic stroke.

Download Full-text