AIMC Topic: Signal Processing, Computer-Assisted
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A machine-learning approach for stress detection using wearable sensors in free-living environments.
Computers in biology and medicine
Jul 18, 2024
Stress is a psychological condition resulting from the body's response to challenging situations, which can negatively impact physical and mental health if experienced over prolonged periods. Early detection of stress is crucial to prevent chronic he...
Comparison of automated deep neural network against manual sleep stage scoring in clinical data.
Computers in biology and medicine
Jul 18, 2024
OBJECTIVE: To compare the accuracy and generalizability of an automated deep neural network and the Philip Sleepware G3™ Somnolyzer system (Somnolyzer) for sleep stage scoring using American Academy of Sleep Medicine (AASM) guidelines.
A Deep Transfer Learning Approach for Sleep Stage Classification and Sleep Apnea Detection Using Wrist-Worn Consumer Sleep Technologies.
IEEE transactions on bio-medical engineering
Jul 18, 2024
Obstructive sleep apnea (OSA) is a common, underdiagnosed sleep-related breathing disorder with serious health implications Objective - We propose a deep transfer learning approach for sleep stage classification and sleep apnea (SA) detection using w...
ECGAN-Assisted ResT-Net Based on Fuzziness for OSA Detection.
IEEE transactions on bio-medical engineering
Jul 18, 2024
OBJECTIVE: Growing attention has been paid recently to electrocardiogram (ECG) based obstructive sleep apnea (OSA) detection, with some progresses been made on this topic. However, the lack of data, low data quality, and incomplete data labeling hind...
Prediction of Left Ventricle Pressure Indices Via a Machine Learning Approach Combining ECG, Pulse Oximetry, and Cardiac Sounds: a Preclinical Feasibility Study.
Journal of cardiovascular translational research
Jul 17, 2024
Heart failure (HF) is defined as the inability of the heart to meet body oxygen demand requiring an elevation in left ventricular filling pressures (LVP) to compensate. LVP increase can be assessed in the cardiac catheterization laboratory, but this ...
Heart Sounds
Phonocardiography
Ventricular Pressure
Heart Failure
Heart Rate
Oximetry
Swine, Miniature
Predictive Value of Tests
Machine Learning
Signal Processing, Computer-Assisted
Animals
Feasibility Studies
Stroke Volume
Ventricular Function, Left
Swine
Electrocardiography
Disease Models, Animal
A novel diagnosis method combined dual-channel SE-ResNet with expert features for inter-patient heartbeat classification.
Medical engineering & physics
Jul 17, 2024
As the number of patients with cardiovascular diseases (CVDs) increases annually, a reliable and automated system for detecting electrocardiogram (ECG) abnormalities is becoming increasingly essential. Scholars have developed numerous methods of arrh...
Delineation of 12-Lead ECG Representative Beats Using Convolutional Encoder-Decoders with Residual and Recurrent Connections.
Sensors (Basel, Switzerland)
Jul 17, 2024
The aim of this study is to address the challenge of 12-lead ECG delineation by different encoder-decoder architectures of deep neural networks (DNNs). This study compares four concepts for encoder-decoders based on a fully convolutional architecture...
Effects of precise cardio sounds on the success rate of phonocardiography.
PloS one
Jul 15, 2024
This work investigates whether inclusion of the low-frequency components of heart sounds can increase the accuracy, sensitivity and specificity of diagnosis of cardiovascular disorders. We standardized the measurement method to minimize changes in si...
Identification and diagnosis of schizophrenia based on multichannel EEG and CNN deep learning model.
Schizophrenia research
Jul 14, 2024
This paper proposes a high-accuracy EEG-based schizophrenia (SZ) detection approach. Unlike comparable literature studies employing conventional machine learning algorithms, our method autonomously extracts the necessary features for network training...
Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities.
Scientific reports
Jul 12, 2024
The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and bio...
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