Combined deep CNN–LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features
Abstract The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) signal and the systolic peak of photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. However, it is difficult to accurately measur...
Guardado en:
Autores principales: | Da Un Jeong, Ki Moo Lim |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/f246113f222c4059ad7f0605fa5391dd |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Simulation Recording of an ECG, PCG, and PPG for Feature Extractions
por: Salma A. Ridha, et al.
Publicado: (2014) -
Simulation Recording of an ECG, PCG, and PPG for Feature Extractions
por: Noor Kamal Al-Qazzaz, et al.
Publicado: (2017) -
Improving Accuracy using The ASERLU layer in CNN-BiLSTM Architecture on Sentiment Analysis
por: Sandi Hermawan, et al.
Publicado: (2021) -
Human Activity Recognition: A Comparative Study to Assess the Contribution Level of Accelerometer, ECG, and PPG Signals
por: Mahsa Sadat Afzali Arani, et al.
Publicado: (2021) -
CNN-LSTM-Based Prognostics of Bidirectional Converters for Electric Vehicles’ Machine
por: Gabriel Rojas-Dueñas, et al.
Publicado: (2021)