AIMC Topic: Signal Processing, Computer-Assisted

Clear Filters Showing 1711 to 1720 of 2081 articles

Comparison of three classifiers in detection of obstruction of the lower urinary tract using recorded sounds of voiding.

Computers in biology and medicine
The aim of this research is to help health care professionals to automatically detect lower urinary tract disorders using sounds of voiding recorded at home. In total 93 patients were diagnosed as obstructed or non-obstructed in a hospital using trad...

Augmenting Common Spatial Patterns to deep learning networks for improved alcoholism detection using EEG signals.

Computers in biology and medicine
One of the main risk factors for numerous health problems is excessive drinking. Alcoholism is a severe disorder that can affect a person's thinking and cognitive abilities. Early detection of alcoholism can help the subject regain control over their...

Myocardial Infarction Detection using Variational Mode Decomposition with Fuzzy Weight Particle Swarm Optimization and Depthwise Separable Convolutional Network.

Computers in biology and medicine
The challenge of precisely recognizing myocardial infarction (MI) from electrocardiographic (ECG) readings stems from the complex nature of these signals.ECG data exhibit both nonlinear and non-stationary properties, making interpretation difficult. ...

Improve robustness to mismatched sampling rate: An alternating deep low-rank approach for exponential function reconstruction and its biomedical magnetic resonance applications.

Journal of magnetic resonance (San Diego, Calif. : 1997)
Undersampling accelerates signal acquisition at the expense of introducing artifacts. Removing these artifacts is a fundamental problem in signal processing and this task is also called signal reconstruction. Through modeling signals as the superimpo...

Deep generative models for physiological signals: A systematic literature review.

Artificial intelligence in medicine
In this paper, we present a systematic literature review on deep generative models for physiological signals, particularly electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG) and electromyogram (EMG). Compared to the existin...

Ternary spike-based neuromorphic signal processing system.

Neural networks : the official journal of the International Neural Network Society
Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fields, resulting in significant enhancements in performance. However, DNNs generally require substantial computational resources, leading to significant ...

[Application of multi-scale spatiotemporal networks in physiological signal and facial action unit measurement].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Multi-task learning (MTL) has demonstrated significant advantages in the field of physiological signal measurement. This approach enhances the model's generalization ability by sharing parameters and features between similar tasks, even in data-scarc...

[Acoustic technology empowers the diagnosis and treatment of respiratory diseases: challenges, and prospects].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Respiratory diseases is a major challenge to global public health. In recent years, acoustic technology has shown great potential as a non-invasive and convenient diagnostic method for detecting and monitoring respiratory diseases. With the developme...

CRT: A Convolutional Recurrent Transformer for Automatic Sleep State Detection.

IEEE journal of biomedical and health informatics
Sleep is a crucial period of rest necessary for optimal cognitive function, psychological well-being, and execution of everyday tasks. In the field of sleep healthcare, the primary objective is to identify and classify the various sleep states. Imple...

Classification of sounds from Pacific white-sided dolphins using a convolutional neural network and a method to reduce false-positive detections.

The Journal of the Acoustical Society of America
An automatic detector for identifying the clicks and pulsed calls of Pacific white-sided dolphins (Lagenorhynchus obliquidens) was developed using a convolutional neural network architecture for passive acoustic monitoring, particularly in the areas ...