OBJECTIVE: Atrial fibrillation (AF) is the most commonly experienced arrhythmia and it increases the risk of stroke and heart failure. The challenge in detecting the presence of AF is the occasional and asymptomatic manifestation of the condition. Long-term monitoring can increase the sensitivity of detecting intermittent AF episodes, however it is either cumbersome or invasive and costly with electrocardiography (ECG). Photoplethysmography (PPG) is an unobtrusive measuring modality enabling heart rate monitoring, and promising results have been presented in detecting AF. However, there is still limited knowledge about the applicability of the PPG solutions in free-living conditions. The aim of this study was to compare the inter-beat interval derived features for AF detection between ECG and wrist-worn PPG in daily life. APPROACH: The data consisted of 24 h ECG, PPG, and accelerometer measurements from 27 patients (eight AF, 19 non-AF). In total, seven features (Shannon entropy, root mean square of successive differences (RMSSD), normalized RMSSD, pNN40, pNN70, sample entropy, and coefficient of sample entropy (CosEn)) were compared. Body movement was measured with the accelerometer and used with three different thresholds to exclude PPG segments affected by movement. MAIN RESULTS: CosEn resulted as the best performing feature from ECG with Cohens kappa 0.95. When the strictest movement threshold was applied, the same performance was obtained with PPG (kappa = 0.96). In addition, pNN40 and pNN70 reached similar results with the same threshold (kappa = 0.95 and 0.94), but were more robust with respect to movement artefacts. The coverage of PPG was 24.0%-57.6% depending on the movement threshold compared to 92.1% of ECG. SIGNIFICANCE: The inter-beat interval features derived from PPG are equivalent to the ones from ECG for AF detection. Movement artefacts substantially worsen PPG-based AF monitoring in free-living conditions, therefore monitoring coverage needs to be carefully selected. Wrist-worn PPG still provides a promising technology for long-term AF monitoring.
OBJECTIVE:Atrial fibrillation (AF) is the most commonly experienced arrhythmia and it increases the risk of stroke and heart failure. The challenge in detecting the presence of AF is the occasional and asymptomatic manifestation of the condition. Long-term monitoring can increase the sensitivity of detecting intermittent AF episodes, however it is either cumbersome or invasive and costly with electrocardiography (ECG). Photoplethysmography (PPG) is an unobtrusive measuring modality enabling heart rate monitoring, and promising results have been presented in detecting AF. However, there is still limited knowledge about the applicability of the PPG solutions in free-living conditions. The aim of this study was to compare the inter-beat interval derived features for AF detection between ECG and wrist-worn PPG in daily life. APPROACH: The data consisted of 24 h ECG, PPG, and accelerometer measurements from 27 patients (eight AF, 19 non-AF). In total, seven features (Shannon entropy, root mean square of successive differences (RMSSD), normalized RMSSD, pNN40, pNN70, sample entropy, and coefficient of sample entropy (CosEn)) were compared. Body movement was measured with the accelerometer and used with three different thresholds to exclude PPG segments affected by movement. MAIN RESULTS: CosEn resulted as the best performing feature from ECG with Cohens kappa 0.95. When the strictest movement threshold was applied, the same performance was obtained with PPG (kappa = 0.96). In addition, pNN40 and pNN70 reached similar results with the same threshold (kappa = 0.95 and 0.94), but were more robust with respect to movement artefacts. The coverage of PPG was 24.0%-57.6% depending on the movement threshold compared to 92.1% of ECG. SIGNIFICANCE: The inter-beat interval features derived from PPG are equivalent to the ones from ECG for AF detection. Movement artefacts substantially worsen PPG-based AF monitoring in free-living conditions, therefore monitoring coverage needs to be carefully selected. Wrist-worn PPG still provides a promising technology for long-term AF monitoring.
Authors: Peter H Charlton; Panicos A Kyriaco; Jonathan Mant; Vaidotas Marozas; Phil Chowienczyk; Jordi Alastruey Journal: Proc IEEE Inst Electr Electron Eng Date: 2022-03-11 Impact factor: 10.961
Authors: Craig J Goergen; MacKenzie J Tweardy; Steven R Steinhubl; Stephan W Wegerich; Karnika Singh; Rebecca J Mieloszyk; Jessilyn Dunn Journal: Annu Rev Biomed Eng Date: 2021-12-21 Impact factor: 11.324
Authors: Fahimeh Mohagheghian; Dong Han; Andrew Peitzsch; Nishat Nishita; Eric Ding; Emily L Dickson; Danielle DiMezza; Edith M Otabil; Kamran Noorishirazi; Jessica Scott; Darleen Lessard; Ziyue Wang; Cody Whitcomb; Khanh-Van Tran; Timothy P Fitzgibbons; David D McManus; Ki H Chon Journal: IEEE Trans Biomed Eng Date: 2022-08-19 Impact factor: 4.756
Authors: Astrid N L Hermans; Rachel M J van der Velden; Monika Gawalko; Dominique V M Verhaert; Lien Desteghe; David Duncker; Martin Manninger; Hein Heidbuchel; Ron Pisters; Martin Hemels; Laurent Pison; Afzal Sohaib; Arian Sultan; Daniel Steven; Petra Wijtvliet; Robert Tieleman; Dhiraj Gupta; Dobromir Dobrev; Emma Svennberg; Harry J G M Crijns; Nikki A H A Pluymaekers; Jeroen M Hendriks; Dominik Linz Journal: Clin Cardiol Date: 2020-10-08 Impact factor: 2.882
Authors: Gabriele B Papini; Pedro Fonseca; Merel M van Gilst; Jan W M Bergmans; Rik Vullings; Sebastiaan Overeem Journal: Sci Rep Date: 2020-08-11 Impact factor: 4.379
Authors: Konstanze Betz; Rachel van der Velden; Monika Gawalko; Astrid Hermans; Nikki Pluymaekers; Henrike A K Hillmann; Jeroen Hendriks; David Duncker; Dominik Linz Journal: Herzschrittmacherther Elektrophysiol Date: 2021-07-24