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Continuous Blood Pressure Estimation Based on Two-Domain Fusion Model
- Source :
- Computational and Mathematical Methods in Medicine, Vol 2018 (2018), Computational and Mathematical Methods in Medicine
- Publication Year :
- 2018
- Publisher :
- Hindawi Limited, 2018.
-
Abstract
- Blood pressure (BP) is one of the indispensable elements of physiological health characteristics and a significant indicator for predicting and diagnosing hypertension and cardiovascular diseases. This paper proposes a two-domain fusion model to estimate BP continuously from pulse wave acquired with a pressure sensor. Method. The optimal external pressure applied on the pressure sensor is first determined in order to capture pulse wave in the radial artery. The captured pulse wave is then processed in both the time and frequency domains via filtering and fast Fourier transform. Finally, a set of features are extracted from these two domains and input into a neural network along with blood pressure values measured by a commercial sphygmomanometer for training. The model is then tested on new data for accuracy evaluation. Results. The proposed two-domain fusion method achieved a high degree of accuracy in measuring blood pressure.
- Subjects :
- Article Subject
Computer science
Acoustics
Transducers
Fast Fourier transform
Blood Pressure
Sphygmomanometer
Pulse Wave Analysis
030204 cardiovascular system & hematology
lcsh:Computer applications to medicine. Medical informatics
General Biochemistry, Genetics and Molecular Biology
03 medical and health sciences
0302 clinical medicine
medicine.artery
medicine
Humans
Pulse wave
Radial artery
Fusion
Models, Statistical
Fourier Analysis
General Immunology and Microbiology
Artificial neural network
Applied Mathematics
Reproducibility of Results
Blood Pressure Determination
General Medicine
Pressure sensor
Blood pressure
Modeling and Simulation
Radial Artery
lcsh:R858-859.7
Neural Networks, Computer
030217 neurology & neurosurgery
Research Article
Subjects
Details
- ISSN :
- 17486718 and 1748670X
- Volume :
- 2018
- Database :
- OpenAIRE
- Journal :
- Computational and Mathematical Methods in Medicine
- Accession number :
- edsair.doi.dedup.....f735b414475b2246d17158345de2cc90