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IJERPH, Vol. 18, Pages 5838: Automated Detection of Hypertension Using Physiological Signals: A Review
Acharya Arterial hypertension (HT) is a chronic condition of elevated blood pressure (BP), which may cause increased incidence of cardiovascular disease, stroke, kidney failure and mortality. If the HT is diagnosed early, effective treatment can control the BP and avert adverse outcomes. Physiological signals like electrocardiography (ECG), photoplethysmography (PPG), heart rate variability (HRV), and ballistocardiography (BCG) can be used to monitor health status but are not directly correlated with BP measurements. The manual detection of HT using these physiological signals is time consuming and prone to human erro...
Source: International Journal of Environmental Research and Public Health - May 29, 2021 Category: Environmental Health Authors: Sharma Rajput Tan Acharya Tags: Review Source Type: research

IJERPH, Vol. 18, Pages 11302: Review of Deep Learning-Based Atrial Fibrillation Detection Studies
Rajendra Acharya Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF. Various machine learning and deep learning (DL) techniques have been developed for the automated detection of AF. In this review, we focused on the automated AF detection models developed using DL techniques. Twenty-four relevant articles published in intern...
Source: International Journal of Environmental Research and Public Health - October 28, 2021 Category: Environmental Health Authors: Fatma Murat Ferhat Sadak Ozal Yildirim Muhammed Talo Ender Murat Murat Karabatak Yakup Demir Ru-San Tan Udyavara Rajendra Acharya Tags: Review Source Type: research