AIMC Topic: Signal Processing, Computer-Assisted

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Electrocardiography Classification with Leaky Integrate-and-Fire Neurons in an Artificial Neural Network-Inspired Spiking Neural Network Framework.

Sensors (Basel, Switzerland) May 26, 2024
Monitoring heart conditions through electrocardiography (ECG) has been the cornerstone of identifying cardiac irregularities. Cardiologists often rely on a detailed analysis of ECG recordings to pinpoint deviations that are indicative of heart anomal...
Neurons Algorithms Humans Electrocardiography Neural Networks, Computer Signal Processing, Computer-Assisted
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Machine learning model with output correction: Towards reliable bradycardia detection in neonates.

Computers in biology and medicine May 25, 2024
Bradycardia is a commonly occurring condition in premature infants, often causing serious consequences and cardiovascular complications. Reliable and accurate detection of bradycardia events is pivotal for timely intervention and effective treatment....
Infant, Premature Infant, Newborn Male Electrocardiography Signal Processing, Computer-Assisted Bradycardia Machine Learning Algorithms Female Humans Neural Networks, Computer
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Robustness of Deep Learning models in electrocardiogram noise detection and classification.

Computer methods and programs in biomedicine May 24, 2024
BACKGROUND AND OBJECTIVE: Automatic electrocardiogram (ECG) signal analysis for heart disease detection has gained significant attention due to busy lifestyles. However, ECG signals are susceptible to noise, which adversely affects the performance of...
Neural Networks, Computer Algorithms Deep Learning Humans Electrocardiography Signal Processing, Computer-Assisted Signal-To-Noise Ratio
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Detection Method of Epileptic Seizures Using a Neural Network Model Based on Multimodal Dual-Stream Networks.

Sensors (Basel, Switzerland) May 24, 2024
Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited recognizable features, and in order to increase the recognizable features ...
Signal Processing, Computer-Assisted Epilepsy Seizures Humans Neural Networks, Computer Algorithms Electroencephalography
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Machine learning of ECG waveforms and cardiac magnetic resonance for response and survival after cardiac resynchronization therapy.

Computers in biology and medicine May 22, 2024
Cardiac resynchronization therapy (CRT) can lead to marked symptom reduction and improved survival in selected patients with heart failure with reduced ejection fraction (HFrEF); however, many candidates for CRT based on clinical guidelines do not ha...
Middle Aged Electrocardiography Magnetic Resonance Imaging Signal Processing, Computer-Assisted Heart Failure Cardiac Resynchronization Therapy Female Humans Aged Machine Learning Male
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Epileptic Seizure Prediction Using Spatiotemporal Feature Fusion on EEG.

International journal of neural systems May 22, 2024
Electroencephalography (EEG) plays a crucial role in epilepsy analysis, and epileptic seizure prediction has significant value for clinical treatment of epilepsy. Currently, prediction methods using Convolutional Neural Network (CNN) primarily focus ...
Signal Processing, Computer-Assisted Humans Neural Networks, Computer Sensitivity and Specificity Electroencephalography Epilepsy Seizures
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Evaluation of EEG Signals by Spectral Peak Methods and Statistical Correlation for Mental State Discrimination Induced by Arithmetic Tasks.

Sensors (Basel, Switzerland) May 22, 2024
Bringing out brain activity through the interpretation of EEG signals is a challenging problem that involves combined methods of signal analysis. The issue of classifying mental states induced by arithmetic tasks can be solved through various classif...
Humans Signal Processing, Computer-Assisted Neural Networks, Computer Adult Discriminant Analysis Algorithms Electroencephalography Male Brain Support Vector Machine Female
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Embedded Machine Learning System for Muscle Patterns Detection in a Patient with Shoulder Disarticulation.

Sensors (Basel, Switzerland) May 21, 2024
The integration of artificial intelligence (AI) models in the classification of electromyographic (EMG) signals represents a significant advancement in the design of control systems for prostheses. This study explores the development of a portable sy...
Adult Male Muscle, Skeletal Signal Processing, Computer-Assisted Electromyography Shoulder Humans Machine Learning
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A novel feature extraction method PSS-CSP for binary motor imagery - based brain-computer interfaces.

Computers in biology and medicine May 20, 2024
In order to improve the performance of binary motor imagery (MI) - based brain-computer interfaces (BCIs) using electroencephalography (EEG), a novel method (PSS-CSP) is proposed, which combines spectral subtraction with common spatial pattern. Spect...
Humans Algorithms Brain Signal Processing, Computer-Assisted Support Vector Machine Brain-Computer Interfaces Imagination Electroencephalography
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Formulation of Common Spatial Patterns for Multi-Task Hyperscanning BCI.

IEEE transactions on bio-medical engineering May 20, 2024
This work proposes a new formulation for common spatial patterns (CSP), often used as a powerful feature extraction technique in brain-computer interfacing (BCI) and other neurological studies. In this approach, applied to multiple subjects' data and...
Algorithms Brain Female Humans Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Adult Male Support Vector Machine
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