AIMC Topic: Signal Processing, Computer-Assisted

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VPNET: Variable Projection Networks.

International journal of neural systems Oct 13, 2021
In this paper, we introduce VPNet, a novel model-driven neural network architecture based on variable projection (VP). Applying VP operators to neural networks results in learnable features, interpretable parameters, and compact network structures. T...
Neural Networks, Computer Signal Processing, Computer-Assisted Electrocardiography Cluster Analysis
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The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

BMC cardiovascular disorders Oct 13, 2021
BACKGROUND: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar electrocardiographic (ECG) patterns, characterized by ST-segment elevation in the right precordial leads, and risk of Sudden Cardiac Death (SCD). Furthe...
Diagnosis, Computer-Assisted Electrocardiography Action Potentials Gene Expression Profiling Transcriptome Workflow Heart Rate Brugada Syndrome Research Design Italy Retrospective Studies Prospective Studies Signal Processing, Computer-Assisted Humans Prognosis Reproducibility of Results Machine Learning Predictive Value of Tests
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Multi-Classification of Complex Microseismic Waveforms Using Convolutional Neural Network: A Case Study in Tunnel Engineering.

Sensors (Basel, Switzerland) Oct 12, 2021
Due to the complexity of the various waveforms of microseismic data, there are high requirements on the automatic multi-classification of such data; an accurate classification is conducive for further signal processing and stability analysis of surro...
Noise Signal Processing, Computer-Assisted Neural Networks, Computer
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EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic (EEG)-based BCI a...
Signal Processing, Computer-Assisted Algorithms Humans Electroencephalography Brain-Computer Interfaces Machine Learning Epilepsy
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Predicting Human Intention-Behavior Through EEG Signal Analysis Using Multi-Scale CNN.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
At present, the application of Electroencephalogram (EEG) signal classification to human intention-behavior prediction has become a hot topic in the brain computer interface (BCI) research field. In recent studies, the introduction of convolutional n...
Signal Processing, Computer-Assisted Intention Brain Neural Networks, Computer Electroencephalography Humans Algorithms
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A Multi-Scale Activity Transition Network for Data Translation in EEG Signals Decoding.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Electroencephalogram (EEG) is a non-invasive collection method for brain signals. It has broad prospects in brain-computer interface (BCI) applications. Recent advances have shown the effectiveness of the widely used convolutional neural network (CNN...
Humans Brain Neural Networks, Computer Electroencephalography Algorithms Signal Processing, Computer-Assisted
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Subject-Independent Emotion Recognition of EEG Signals Based on Dynamic Empirical Convolutional Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Affective computing is one of the key technologies to achieve advanced brain-machine interfacing. It is increasingly concerning research orientation in the field of artificial intelligence. Emotion recognition is closely related to affective computin...
Male Emotions Signal Processing, Computer-Assisted Entropy Electroencephalography Algorithms Brain Humans Female Neural Networks, Computer
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Advanced Machine-Learning Methods for Brain-Computer Interfacing.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
The brain-computer interface (BCI) connects the brain and the external world through an information transmission channel by interpreting the physiological information of the brain during thinking activities. The effective classification of electroenc...
Male Electroencephalography Adult Brain-Computer Interfaces Imagination Signal Processing, Computer-Assisted Algorithms Female Humans Young Adult Machine Learning
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A Hierarchical Discriminative Sparse Representation Classifier for EEG Signal Detection.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
Classification of electroencephalogram (EEG) signal data plays a vital role in epilepsy detection. Recently sparse representation-based classification (SRC) methods have achieved the good performance in EEG signal automatic detection, by which the EE...
Electroencephalography Epilepsy Signal Processing, Computer-Assisted Algorithms Humans Neural Networks, Computer Brain Deep Learning
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Epilepsy Signal Recognition Using Online Transfer TSK Fuzzy Classifier Underlying Classification Error and Joint Distribution Consensus Regularization.

IEEE/ACM transactions on computational biology and bioinformatics Oct 7, 2021
In this study, an online transfer TSK fuzzy classifier O-T-TSK-FC is proposed for recognizing epilepsy signals. Compared with most of the existing transfer learning models, O-T-TSK-FC enjoys its merits from the following three aspects: 1) Since diffe...
Fuzzy Logic Electroencephalography Epilepsy Algorithms Consensus Signal Processing, Computer-Assisted Humans Machine Learning
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