Continuous Atrial Fibrillation Monitoring From Photoplethysmography: Comparison Between Supervised Deep Learning and Heuristic Signal Processing.
JACC Clin Electrophysiol
; 10(2): 334-345, 2024 Feb.
Article
em En
| MEDLINE
| ID: mdl-38340117
ABSTRACT
BACKGROUND:
Continuous monitoring for atrial fibrillation (AF) using photoplethysmography (PPG) from smartwatches or other wearables is challenging due to periods of poor signal quality during motion or suboptimal wearing. As a result, many consumer wearables sample infrequently and only analyze when the user is at rest, which limits the ability to perform continuous monitoring or to quantify AF.OBJECTIVES:
This study aimed to compare 2 methods of continuous monitoring for AF in free-living patients a well-validated signal processing (SP) heuristic and a convolutional deep neural network (DNN) trained on raw signal.METHODS:
We collected 4 weeks of continuous PPG and electrocardiography signals in 204 free-living patients. Both SP and DNN models were developed and validated both on holdout patients and an external validation set.RESULTS:
The results show that the SP model demonstrated receiver-operating characteristic area under the curve (AUC) of 0.972 (sensitivity 99.6%, specificity 94.4%), which was similar to the DNN receiver-operating characteristic AUC of 0.973 (sensitivity 92.2, specificity 95.5%); however, the DNN classified significantly more data (95% vs 62%), revealing its superior tolerance of tracings prone to motion artifact. Explainability analysis revealed that the DNN automatically suppresses motion artifacts, evaluates irregularity, and learns natural AF interbeat variability. The DNN performed better and analyzed more signal in the external validation cohort using a different population and PPG sensor (AUC, 0.994; 97% analyzed vs AUC, 0.989; 88% analyzed).CONCLUSIONS:
DNNs perform at least as well as SP models, classify more data, and thus may be better for continuous PPG monitoring.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Fibrilação Atrial
/
Aprendizado Profundo
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
JACC Clin Electrophysiol
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos
País de publicação:
Estados Unidos