Literature DB >> 28836507

Detection of atrial fibrillation using an earlobe photoplethysmographic sensor.

Thomas Conroy1, Jairo Hernandez Guzman, Burr Hall, Gill Tsouri, Jean-Philippe Couderc.   

Abstract

Atrial fibrillation (AF) is the most common cardiac arrhythmia in the world, associated with increased risk of thromboembolic events and an increased mortality rate. In addition, a significant portion of AF patients are asymptomatic. Current AF diagnostic methods, often including a body surface electrocardiogram or implantable loop recorder, are both expensive and invasive and offer limited access within the general community.
OBJECTIVE: We tested the feasibility of the detection of AF using a photoplethysmographic signal acquired from an inexpensive, non-invasive earlobe photoplethysmographic sensor. This technology can be implemented into wearable devices and would enable continuous cardiac monitoring capabilities, greatly improving the rate of asymptomatic AF detection. APPROACH: We conducted a clinical study of patients going through electrical cardioversion for AF treatment. Photoplethysmographic recordings were taken from these AF patients before and after their cardioversion procedure, along with recordings from a healthy control group. Using these recordings, cardiac beats were identified and the inter-systolic interval was calculated. The inter-systolic interval was used to calculate four parameters to quantify the heart rate variability indicative of AF. Receiver operating characteristic curves were used to calculate discriminant thresholds between the AF and non-AF cohorts. MAIN
RESULTS: The parameter with the greatest discriminant capability resulted in a sensitivity and specificity of 90.9%. These results are comparable to expensive ECG-based and invasive implantable loop recorder AF detection methods. SIGNIFICANCE: These results demonstrate that using a non-invasive earlobe photoplethysmographic signal is a viable and inexpensive alternative to ECG-based AF detection methods, and an alternative that could be invaluable in detecting subclinical AF.

Entities:  

Mesh:

Year:  2017        PMID: 28836507     DOI: 10.1088/1361-6579/aa8830

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  11 in total

1.  Can one detect atrial fibrillation using a wrist-type photoplethysmographic device?

Authors:  Sibylle Fallet; Mathieu Lemay; Philippe Renevey; Célestin Leupi; Etienne Pruvot; Jean-Marc Vesin
Journal:  Med Biol Eng Comput       Date:  2018-09-15       Impact factor: 2.602

2.  Noninvasive Continuous Monitoring of Vital Signs With Wearables: Fit for Medical Use?

Authors:  Malte Jacobsen; Till A Dembek; Guido Kobbe; Peter W Gaidzik; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2020-02-17

3.  2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society.

Authors:  Niraj Varma; Iwona Cygankiewicz; Mintu P Turakhia; Hein Heidbuchel; Yu-Feng Hu; Lin Yee Chen; Jean-Philippe Couderc; Edmond M Cronin; Jerry D Estep; Lars Grieten; Deirdre A Lane; Reena Mehra; Alex Page; Rod Passman; Jonathan P Piccini; Ewa Piotrowicz; Ryszard Piotrowicz; Pyotr G Platonov; Antonio Luiz Ribeiro; Robert E Rich; Andrea M Russo; David Slotwiner; Jonathan S Steinberg; Emma Svennberg
Journal:  Circ Arrhythm Electrophysiol       Date:  2021-02-12

4.  2021 ISHNE/HRS/EHRA/APHRS Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia Pacific Heart Rhythm Society.

Authors:  Niraj Varma; Iwona Cygankiewicz; Mintu P Turakhia; Hein Heidbuchel; Yufeng Hu; Lin Yee Chen; Jean-Philippe Couderc; Edmond M Cronin; Jerry D Estep; Lars Grieten; Deirdre A Lane; Reena Mehra; Alex Page; Rod Passman; Jonathan P Piccini; Ewa Piotrowicz; Ryszard Piotrowicz; Pyotr G Platonov; Antonio Luiz Ribeiro; Robert E Rich; Andrea M Russo; David Slotwiner; Jonathan S Steinberg; Emma Svennberg
Journal:  Cardiovasc Digit Health J       Date:  2021-01-29

5.  Visual Reassessment with Flux-Interval Plot Configuration after Automatic Classification for Accurate Atrial Fibrillation Detection by Photoplethysmography.

Authors:  Justin Chu; Wen-Tse Yang; Yao-Ting Chang; Fu-Liang Yang
Journal:  Diagnostics (Basel)       Date:  2022-05-24

6.  Detection of Atrial Fibrillation Using a Ring-Type Wearable Device (CardioTracker) and Deep Learning Analysis of Photoplethysmography Signals: Prospective Observational Proof-of-Concept Study.

Authors:  Soonil Kwon; Joonki Hong; Eue-Keun Choi; Byunghwan Lee; Changhyun Baik; Euijae Lee; Eui-Rim Jeong; Bon-Kwon Koo; Seil Oh; Yung Yi
Journal:  J Med Internet Res       Date:  2020-05-21       Impact factor: 5.428

7.  Deep Learning Approaches to Detect Atrial Fibrillation Using Photoplethysmographic Signals: Algorithms Development Study.

Authors:  Soonil Kwon; Joonki Hong; Eue-Keun Choi; Euijae Lee; David Earl Hostallero; Wan Ju Kang; Byunghwan Lee; Eui-Rim Jeong; Bon-Kwon Koo; Seil Oh; Yung Yi
Journal:  JMIR Mhealth Uhealth       Date:  2019-06-06       Impact factor: 4.773

Review 8.  Photoplethysmography based atrial fibrillation detection: a review.

Authors:  Tania Pereira; Nate Tran; Kais Gadhoumi; Michele M Pelter; Duc H Do; Randall J Lee; Rene Colorado; Karl Meisel; Xiao Hu
Journal:  NPJ Digit Med       Date:  2020-01-10

9.  Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo-Plethysmography at the Wrist.

Authors:  Alberto G Bonomi; Fons Schipper; Linda M Eerikäinen; Jenny Margarito; Ralph van Dinther; Guido Muesch; Helma M de Morree; Ronald M Aarts; Saeed Babaeizadeh; David D McManus; Lukas R C Dekker
Journal:  J Am Heart Assoc       Date:  2018-08-07       Impact factor: 5.501

10.  Analysis of Relevant Features from Photoplethysmographic Signals for Atrial Fibrillation Classification.

Authors:  César A Millán; Nathalia A Girón; Diego M Lopez
Journal:  Int J Environ Res Public Health       Date:  2020-01-13       Impact factor: 3.390

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