AIMC Topic: Signal Processing, Computer-Assisted

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Amplitude-Time Dual-View Fused EEG Temporal Feature Learning for Automatic Sleep Staging.

IEEE transactions on neural networks and learning systems May 2, 2024
Electroencephalogram (EEG) plays an important role in studying brain function and human cognitive performance, and the recognition of EEG signals is vital to develop an automatic sleep staging system. However, due to the complex nonstationary charact...
Signal Processing, Computer-Assisted Humans Sleep Stages Neural Networks, Computer Algorithms Machine Learning Adult Female Male Young Adult Electroencephalography
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Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data.

Sensors (Basel, Switzerland) May 1, 2024
Bats play a pivotal role in maintaining ecological balance, and studying their behaviors offers vital insights into environmental health and aids in conservation efforts. Determining the presence of various bat species in an environment is essential ...
Neural Networks, Computer Animals Vocalization, Animal Signal Processing, Computer-Assisted Chiroptera Acoustics Echolocation
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Calibrating Deep Learning Classifiers for Patient-Independent Electroencephalogram Seizure Forecasting.

Sensors (Basel, Switzerland) Apr 30, 2024
The recent scientific literature abounds in proposals of seizure forecasting methods that exploit machine learning to automatically analyze electroencephalogram (EEG) signals. Deep learning algorithms seem to achieve a particularly remarkable perform...
Calibration Humans Machine Learning Epilepsy Algorithms Seizures Deep Learning Signal Processing, Computer-Assisted Electroencephalography
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Emotion recognition with reduced channels using CWT based EEG feature representation and a CNN classifier.

Biomedical physics & engineering express Apr 30, 2024
Although emotion recognition has been studied for decades, a more accurate classification method that requires less computing is still needed. At present, in many studies, EEG features are extracted from all channels to recognize emotional states, ho...
Neural Networks, Computer Algorithms Emotions Humans Entropy Arousal Electroencephalography Signal Processing, Computer-Assisted Wavelet Analysis
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Expert-level sleep staging using an electrocardiography-only feed-forward neural network.

Computers in biology and medicine Apr 29, 2024
Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomno...
Sleep Stages Adult Electrocardiography Adolescent Male Female Signal Processing, Computer-Assisted Child, Preschool Middle Aged Aged Polysomnography Child Aged, 80 and over Humans Neural Networks, Computer
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Mapping Method of Human Arm Motion Based on Surface Electromyography Signals.

Sensors (Basel, Switzerland) Apr 29, 2024
This paper investigates a method for precise mapping of human arm movements using sEMG signals. A multi-channel approach captures the sEMG signals, which, combined with the accurately calculated joint angles from an Inertial Measurement Unit, allows ...
Gestures Signal Processing, Computer-Assisted Electromyography Arm Movement Algorithms Adult Male Humans Neural Networks, Computer
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Arrhythmia detection by the graph convolution network and a proposed structure for communication between cardiac leads.

BMC medical research methodology Apr 27, 2024
One of the most common causes of death worldwide is heart disease, including arrhythmia. Today, sciences such as artificial intelligence and medical statistics are looking for methods and models for correct and automatic diagnosis of cardiac arrhythm...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Neural Networks, Computer Algorithms Electrocardiography Humans
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A hybrid 1D CNN-BiLSTM model for epileptic seizure detection using multichannel EEG feature fusion.

Biomedical physics & engineering express Apr 26, 2024
Epilepsy, a chronic non-communicable disease is characterized by repeated unprovoked seizures, which are transient episodes of abnormal electrical activity in the brain. While Electroencephalography (EEG) is considered as the gold standard for diagno...
Seizures Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms Brain Reproducibility of Results Electroencephalography Epilepsy Humans
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Attention-based convolutional neural network with multi-modal temporal information fusion for motor imagery EEG decoding.

Computers in biology and medicine Apr 24, 2024
Convolutional neural network (CNN) has been widely applied in motor imagery (MI)-based brain computer interface (BCI) to decode electroencephalography (EEG) signals. However, due to the limited perceptual field of convolutional kernel, CNN only extra...
Humans Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Neural Networks, Computer Deep Learning Electroencephalography
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Autism spectrum disorder diagnosis with EEG signals using time series maps of brain functional connectivity and a combined CNN-LSTM model.

Computer methods and programs in biomedicine Apr 24, 2024
BACKGROUND AND OBJECTIVE: People with autism spectrum disorder (ASD) often have cognitive impairments. Effective connectivity between different areas of the brain is essential for normal cognition. Electroencephalography (EEG) has been widely used in...
Humans Adolescent Neural Networks, Computer Brain Child Electroencephalography Algorithms Female Brain Mapping Signal Processing, Computer-Assisted Autism Spectrum Disorder Male
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