AIMC Topic: Heart Rate
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Estimating intra- and inter-subject oxygen consumption in outdoor human gait using multiple neural network approaches.
PloS one
Sep 27, 2024
Oxygen consumption ([Formula: see text]) is an important measure for exercise test, such as walking and running, that can be measured outdoors using portable spirometers or metabolic analyzers. However, these devices are not feasible for regular use ...
Inferring ECG Waveforms from PPG Signals with a Modified U-Net Neural Network.
Sensors (Basel, Switzerland)
Sep 19, 2024
There are two widely used methods to measure the cardiac cycle and obtain heart rate measurements: the electrocardiogram (ECG) and the photoplethysmogram (PPG). The sensors used in these methods have gained great popularity in wearable devices, which...
Fed-CL- an atrial fibrillation prediction system using ECG signals employing federated learning mechanism.
Scientific reports
Sep 9, 2024
Deep learning has shown great promise in predicting Atrial Fibrillation using ECG signals and other vital signs. However, a major hurdle lies in the privacy concerns surrounding these datasets, which often contain sensitive patient information. Balan...
A Generalisable Heartbeat Classifier Leveraging Self-Supervised Learning for ECG Analysis During Magnetic Resonance Imaging.
IEEE journal of biomedical and health informatics
Sep 5, 2024
Electrocardiogram (ECG) is acquired during Magnetic Resonance Imaging (MRI) to monitor patients and synchronize image acquisition with the heart motion. ECG signals are highly distorted during MRI due to the complex electromagnetic environment. Autom...
Enhancing Heart Failure Care: Deep Learning-Based Activity Classification in Left Ventricular Assist Device Patients.
ASAIO journal (American Society for Artificial Internal Organs : 1992)
Sep 4, 2024
Accurate activity classification is essential for the advancement of closed-loop control for left ventricular assist devices (LVADs), as it provides necessary feedback to adapt device operation to the patient's current state. Therefore, this study ai...
Enhancing Sports Injury Risk Assessment in Soccer Through Machine Learning and Training Load Analysis.
Journal of sports science & medicine
Sep 1, 2024
Sports injuries pose significant challenges in athlete welfare and team dynamics, particularly in high-intensity sports like soccer. This study used machine learning algorithms to assess non-contact injury risk in professional male soccer players fro...
Electrocardiogram-Based Artificial Intelligence to Discriminate Cardioembolic Stroke and Stratify Risk of Atrial Fibrillation After Stroke.
Circulation. Arrhythmia and electrophysiology
Aug 28, 2024
ECG classification via integration of adaptive beat segmentation and relative heart rate with deep learning networks.
Computers in biology and medicine
Aug 27, 2024
We propose a state-of-the-art deep learning approach for accurate electrocardiogram (ECG) signal analysis, addressing both waveform delineation and beat type classification tasks. For beat type classification, we integrated two novel schemes into the...
Artificial Intelligence-Driven Prognosis of Respiratory Mechanics: Forecasting Tissue Hysteresivity Using Long Short-Term Memory and Continuous Sensor Data.
Sensors (Basel, Switzerland)
Aug 27, 2024
Tissue hysteresivity is an important marker for determining the onset and progression of respiratory diseases, calculated from forced oscillation lung function test data. This study aims to reduce the number and duration of required measurements by c...
Enhanced machine learning approaches for OSA patient screening: model development and validation study.
Scientific reports
Aug 26, 2024
Age, gender, body mass index (BMI), and mean heart rate during sleep were found to be risk factors for obstructive sleep apnea (OSA), and a variety of methods have been applied to predict the occurrence of OSA. This study aimed to develop and evaluat...
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