AIMC Topic: Signal Processing, Computer-Assisted

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Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection.

Scientific reports Jul 1, 2025
Schizophrenia is a mental disorder characterized by hallucinations, delusions, disorganized thinking and behavior, and inappropriate affect. Early and accurate diagnosis of schizophrenia remains a challenge due to the disorder's complex nature and th...
Signal Processing, Computer-Assisted Schizophrenia Support Vector Machine Electroencephalography Humans Algorithms Female Adult Male
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Towards decoding motor imagery from EEG signal using optimized back propagation neural network with honey badger algorithm.

Scientific reports Jul 1, 2025
The importance of using Brain-Computer Interface (BCI) systems based on electro encephalography (EEG) signal to decode Motor Imagery(MI) is very impressive because of the possibility of analyzing and translating brain signals related to movement inte...
Movement Imagination Neural Networks, Computer Algorithms Brain Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans
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Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach.

Scientific reports Jul 1, 2025
Schizophrenia is a persistent and serious mental illness that leads to distortions in cognition, perception, emotions, speech, self-awareness, and actions. Affecting about 1% of people worldwide, schizophrenia usually emerges in late adolescence or e...
Humans Machine Learning Brain Deep Learning Electroencephalography Signal Processing, Computer-Assisted Female Adult Male Schizophrenia
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Ensemble learning for biomedical signal classification: a high-accuracy framework using spectrograms from percussion and palpation.

Scientific reports Jul 1, 2025
Accurate classification of biomedical signals is crucial for advancing non-invasive diagnostic methods, particularly for identifying gastrointestinal and related medical conditions where conventional techniques often fall short. An ensemble learning ...
Support Vector Machine Signal Processing, Computer-Assisted Fourier Analysis Ensemble Learning Palpation Percussion Neural Networks, Computer Machine Learning Algorithms Humans
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Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism.

Scientific reports Jul 1, 2025
Blood pressure (BP) serves as a fundamental indicator of cardiovascular health, measuring the force exerted by circulating blood against arterial walls during each heartbeat. This paper introduces an advanced deep learning framework for precise, non-...
Female Male Middle Aged Humans Neural Networks, Computer Blood Pressure Determination Blood Pressure Signal Processing, Computer-Assisted Deep Learning Wearable Electronic Devices Photoplethysmography
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A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection.

PloS one Jun 26, 2025
Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain activity, which can severely affects people's normal lives. To improve the lives of these patients, it is necessary to develop accurate methods to predic...
Humans Neural Networks, Computer Signal Processing, Computer-Assisted Electroencephalography Algorithms Epilepsy Deep Learning Seizures
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Epilepsy Prediction via Time-Frequency Features and Multi-Scale Hybrid Neural Networks.

Journal of medical systems Jun 25, 2025
The prediction of epileptic seizures heavily depends on the precise embedding and classification of complex, multi-dimensional electroencephalogram (EEG) signals. Due to individual variability and the dynamic non-linear nature of EEG signals, extract...
Neural Networks, Computer Electroencephalography Epilepsy Humans Signal Processing, Computer-Assisted
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Recognition of common shortwave protocols and their subcarrier modulations based on multi-scale convolutional GRU.

PloS one Jun 24, 2025
Shortwave communication plays a vital role in disaster relief and remote communications due to its long-range capabilities and resilience to interference. However, challenges such as multipath propagation, frequency-selective fading, and low signal-t...
Signal Processing, Computer-Assisted Signal-To-Noise Ratio Humans Algorithms Deep Learning
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Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

PloS one Jun 17, 2025
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variabi...
Convolutional Neural Networks Algorithms Electrocardiography Signal Processing, Computer-Assisted Humans Databases, Factual Neural Networks, Computer Arrhythmias, Cardiac Deep Learning
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation.

PloS one Jun 13, 2025
INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...
Humans Neural Networks, Computer Polysomnography Electroencephalography Sleep Deprivation Algorithms Female Signal Processing, Computer-Assisted Adult Wavelet Analysis Male
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