Classification of Fetal Heart Rate Based on Poincare Plot and LSTM / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 250-255, 2021.
Artículo
en Chino
| WPRIM
| ID: wpr-880461
ABSTRACT
Fetal heart rate plays an essential role in maternal and fetal monitoring and fetal health detection. In this study, a method based on Poincare Plot and LSTM is proposed to realize the high performance classification of abnormal fetal heart rate. Firstly, the original fetal heart rate signal of CTU-UHB database is preprocessed via interpolation, then the sequential fetal heart rate signal is converted into Poincare Plot to obtain nonlinear characteristics of the signals, and then SquenzeNet is used to extract the features of Poincare Plot. Finally, the features extracted by SqueezeNet are classified by LSTM. And the accuracy, the true positive rate and the false positive rate are 98.00%, 100.00%, 92.30% respectively on 2 000 test set data. Compared with the traditional fetal heart rate classification method, all respects are improved. The method proposed in this study has good performance in CTU-UHB fetal monitoring database and has certain practical value in the clinical diagnosis of auxiliary fetal heart rate detection.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Frecuencia Cardíaca Fetal
/
Bases de Datos Factuales
/
Monitoreo Fetal
/
Feto
Límite:
Femenino
/
Humanos
/
Embarazo
Idioma:
Chino
Revista:
Chinese Journal of Medical Instrumentation
Año:
2021
Tipo del documento:
Artículo
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