AIMC Topic: Blood Pressure

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Blood Pressure Estimation Using Time Domain Features of Auscultatory Waveforms and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a novel method to estimate systolic blood pressure (SBP) and diastolic blood pressure (DBP) from time domain features extracted on auscultatory waveforms (AWs) using a long short term memory (LSTM) recurrent neural network (RNN). ...

Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The absolute risk reduction (ARR) in cardiovascular events from therapy is generally assumed to be proportional to baseline risk-such that high-risk patients benefit most. Yet newer analyses have proposed using randomized trial data to de...

Deep learning-based automatic blood pressure measurement: evaluation of the effect of deep breathing, talking and arm movement.

Annals of medicine
It is clinically important to evaluate the performance of a newly developed blood pressure (BP) measurement method under different measurement conditions. This study aims to evaluate the performance of using deep learning-based method to measure BPs...

Estimating Systolic Blood Pressure Using Convolutional Neural Networks.

Studies in health technology and informatics
Continuous blood pressure (BP) monitoring can produce a significant amount of digital data, which increases the chance of early diagnosis and improve the rate of survival for people diagnosed with hypertension and Cardiovascular diseases (CVDs). Howe...

Detecting central hypovolemia in simulated hypovolemic shock by automated feature extraction with principal component analysis.

Physiological reports
Assessment of the volume status by blood pressure (BP) monitoring is difficult, since baroreflex control of BP makes it insensitive to blood loss up to about one liter. We hypothesized that a machine learning model recognizes the progression of centr...

Nonlinear System Identification Based on Convolutional Neural Networks for Multiple Drug Interactions.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In heart failure patients, hemodynamics can be regulated by therapeutic drugs. Although the cardiovascular responses to these drugs usually include nonlinearity and drug interactions, it is difficult to identify the characteristics of the dynamics un...

Variation of the Korotkoff Stethoscope Sounds During Blood Pressure Measurement: Analysis Using a Convolutional Neural Network.

IEEE journal of biomedical and health informatics
Korotkoff sounds are known to change their characteristics during blood pressure (BP) measurement, resulting in some uncertainties for systolic and diastolic pressure (SBP and DBP) determinations. The aim of this study was to assess the variation of ...

Arterial stiffness and 25-hydroxyvitamin D levels in chronic kidney disease patients.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: Arterial stiffness refers to arterial wall rigidity, particularly developing in central vessels. Arterial stiffness increases in early stage chronic kidney disease (CKD), and it is a strong predictor of cardiovascular and all cause mortali...

[Noninvasive Continuous Blood Pressure Measurement Method Based on EEMD and ANN].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Blood pressure is an important index to measure the function of human cardiovascular system. In order to solve the problem of non-invasive continuous measurement of blood pressure in electronic sphygmomanometer, a noninvasive blood pressure measureme...