We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analy...
INTRODUCTION: With the widespread availability of portable electrocardiogram (ECG) devices, there will be a surge in ECG diagnoses. Traditional computer-aided diagnosis of arrhythmia mainly relies on the rules of medical knowledge, which are insuffic...
Computational intelligence and neuroscience
Aug 11, 2022
Automated ECG-based arrhythmia detection is critical for early cardiac disease prevention and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia detection with great success. However, the lack of labeled ECG data an...
Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost importance to be able to efficiently diagnose these arrhythmias promptly. There exist many techniques for the detection of arrhythmias; however, the most widely a...
This study proposes a U-net shaped Deep Neural Network (DNN) model to extract remote photoplethysmography (rPPG) signals from skin color signals to estimate Pulse Rate (PR).Three input window sizes are used in the DNN: 256 samples (5.12 s), 512 sampl...
Arterial stiffness due to vascular aging is a major indicator during the assessment of cardiovascular risk. In this study, we propose a method for age estimation by applying deep learning to a photoplethysmogram (PPG) for the non-invasive assessment ...
Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These arrhythmias can lead to potentially deadly consequences, putting your life in jeopardy. As a result, arrhythmia identification and classification are a...
IEEE journal of biomedical and health informatics
Jul 1, 2022
Previous research showed that frailty can influence autonomic nervous system and consequently heart rate response to physical activities, which can ultimately influence the homeostatic state among older adults. While most studies have focused on rest...
IEEE journal of biomedical and health informatics
Jul 1, 2022
The purpose of this study was to confirm the potential of XGBoost as a vascular aging assessment model based on the photoplethysmogram (PPG) features suggested in previous studies, and to explore the key PPG features for vascular aging assessment thr...
Stroke is the second leading cause of death globally after ischemic heart disease, also a risk factor of cardioembolic stroke. Thus, we postulate that heartbeats encapsulate vital signals related to stroke. With the rapid advancement of deep neural n...