brought to you by the Global Hypertension Awareness, a Danish nonprofit organization (reg. # 45145409)

Deep Neural Networks Developed for Blood Pressure Classification

Share:
blood pressure me

In order to diagnose and monitor cardiovascular diseases (CVD), blood pressure must be measured in a convenient and uninterrupted manner. Since hypertension is a sudden health problem that does not exhibit symptoms until late stages of the disease, it is the main risk factor for CVD. Researchers tested whether deep neural networks can discriminate between hypertensive and healthy subjects based on photoplethysmography (PPG) recordings, rather than electrocardiograms (ECG). They also avoided manually extracting features from morphological features, as in previous studies. 50 patients’ simultaneous PPG and arterial blood pressure (ABP) recordings were analyzed. With GoogleLeNet, ResNet-18 and ResNet-50 prestrained convolutional neural networks (CNN), the scalogram of PPG segments obtained by continuous wavelet transformation (CWT) was used as input images for classification

Related Articles

US Surgeon General Dr. Vivek H. Murthy
News
US Surgeon General Calls to Action to Control Hypertension
cvd risk analysis
News
Risk of Heart Attack and Stroke Recalculated
machine learning for blood pressure developed
News
ML Developed at Yale To Personalize Blood Pressure Treatment
stroke occur more often among young adults
News
Significant Increase In Stroke Incidence Among Those Under 55
The Global Hypertension Awareness is a Danish nonprofit. Contact us here
Stay Informed with
Global Hypertension Awareness!

Get Exclusive Content and Breaking News!

Stay Informed with GHA Weekly Newsletter!

Get Exclusive Content and Breaking News Delivered to Your Inbox Daily!

Contact GHA

Get Exclusive Content and Breaking News Delivered to Your Inbox Daily!