An Intelligent Heartbeat Classification System Based on Attributable Features with AdaBoost+Random Forest Algorithm.
J Healthc Eng
; 2021: 9913127, 2021.
Article
em En
| MEDLINE
| ID: mdl-34336169
ABSTRACT
Arrhythmia is a common cardiovascular disease that can threaten human life. In order to assist doctors in accurately diagnosing arrhythmia, an intelligent heartbeat classification system based on the selected optimal feature sets and AdaBoost + Random Forest model is developed. This system can acquire ECG signals through the Holter and transmit them to the cloud platform for preprocessing and feature extraction, and the features are input into AdaBoost + Random Forest for heartbeat classification. The analysis results are output in the form of reports. In this system, by comparing and analyzing the classification accuracy of different feature sets and classifiers, the optimal classification algorithm is obtained and applied to the system. The algorithm accuracy of the system is tested based on the MIT-BIH data set. The result shows that AdaBoost + Random Forest achieved 99.11% accuracy with optimal feature sets. The intelligent heartbeat classification system based on this algorithm has also achieved good results on clinical data.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Sinais Assistido por Computador
/
Eletrocardiografia
Tipo de estudo:
Clinical_trials
/
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
J Healthc Eng
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
China