AIMC Topic: Imagination

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Large AI Models in Health Informatics: Applications, Challenges, and the Future.

IEEE journal of biomedical and health informatics Dec 5, 2023
Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in vario...
Humans Robotics Medical Informatics Imagination Public Health Computational Biology
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Spatio-Temporal Explanation of 3D-EEGNet for Motor Imagery EEG Classification Using Permutation and Saliency.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 16, 2023
Recently, convolutional neural network (CNN)-based classification models have shown good performance for motor imagery (MI) brain-computer interfaces (BCI) using electroencephalogram (EEG) in end-to-end learning. Although a few explainable artificial...
Learning Electroencephalography Artificial Intelligence Brain-Computer Interfaces Algorithms Imagination Humans Neural Networks, Computer
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Hybrid optimization assisted channel selection of EEG for deep learning model-based classification of motor imagery task.

Biomedizinische Technik. Biomedical engineering Nov 8, 2023
OBJECTIVES: To design and develop an approach named HC + SMA-SSA scheme for classifying motor imagery task.
Imagination Signal Processing, Computer-Assisted Brain-Computer Interfaces Deep Learning Electroencephalography Algorithms
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IMH-Net: a convolutional neural network for end-to-end EEG motor imagery classification.

Computer methods in biomechanics and biomedical engineering Nov 7, 2023
As the main component of Brain-computer interface (BCI) technology, the classification algorithm based on EEG has developed rapidly. The previous algorithms were often based on subject-dependent settings, resulting in BCI needing to be calibrated for...
Humans Brain-Computer Interfaces Imagination Electroencephalography Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms
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ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data.

Computers in biology and medicine Nov 2, 2023
OBJECTIVE: Bio-Signals such as electroencephalography (EEG) and electromyography (EMG) are widely used for the rehabilitation of physically disabled people and for the characterization of cognitive impairments. Successful decoding of these bio-signal...
Machine Learning Algorithms Humans Neural Networks, Computer Movement Imagination Electroencephalography Brain-Computer Interfaces
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A novel method for modeling effective connections between brain regions based on EEG signals and graph neural networks for motor imagery detection.

Computer methods in biomechanics and biomedical engineering Aug 7, 2023
Classified as biomedical signal processing, cerebral signal processing plays a key role in human-computer interaction (HCI) and medical diagnosis. The motor imagery (MI) problem is an important research area in this field. Accurate solutions to this ...
Brain Electroencephalography Signal Processing, Computer-Assisted Imagination Humans Neural Networks, Computer
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EEG motor imagery classification using deep learning approaches in naïve BCI users.

Biomedical physics & engineering express Jun 23, 2023
Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to different factors related to the fatigue, substance consumption, concentration, and experience in the ...
Brain-Computer Interfaces Imagination Humans Deep Learning Electroencephalography Reproducibility of Results
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Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism.

Medical & biological engineering & computing Apr 25, 2023
Due to high computational requirements, deep-learning decoders for motor imaginary (MI) electroencephalography (EEG) signals are usually implemented on bulky and heavy computing devices that are inconvenient for physical actions. To date, the applica...
Humans Neural Networks, Computer Imagination Algorithms Electroencephalography Deep Learning Brain-Computer Interfaces
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Multi-band spatial feature extraction and classification for motor imaging EEG signals based on OSFBCSP-GAO-SVM model : EEG signal processing.

Medical & biological engineering & computing Feb 23, 2023
Electroencephalogram (EEG) is a non-stationary random signal with strong background noise, which makes its feature extraction difficult and recognition rate low. This paper presents a feature extraction and classification model of motor imagery EEG s...
Brain-Computer Interfaces Imagination Electroencephalography Signal Processing, Computer-Assisted Algorithms Support Vector Machine
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Classification of BCI Multiclass Motor Imagery Task Based on Artificial Neural Network.

Clinical EEG and neuroscience Jan 5, 2023
Motor imagery (MI) signals recorded by electroencephalography provide the most practical basis for conceiving brain-computer interfaces (BCI). These interfaces offer a high degree of freedom. This helps people with motor disabilities communicate with...
Algorithms Brain Humans Neural Networks, Computer Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Discriminant Analysis Electroencephalography
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