AIMC Topic: Signal Processing, Computer-Assisted

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An efficient ANN SoC for detecting Alzheimer's disease based on recurrent computing.

Computers in biology and medicine Aug 21, 2024
Alzheimer's Disease (AD) is an irreversible, degenerative condition that, while incurable, can have its progression slowed or impeded. While there are numerous methods utilizing neural networks for AD detection, there is a scarcity of High-performanc...
Humans Neural Networks, Computer Female Diagnosis, Computer-Assisted Electroencephalography Aged Male Signal Processing, Computer-Assisted Alzheimer Disease
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Continual learning for seizure prediction via memory projection strategy.

Computers in biology and medicine Aug 21, 2024
Despite extensive algorithms for epilepsy prediction via machine learning, most models are tailored for offline scenarios and cannot handle actual scenarios where data changes over time. Catastrophic forgetting(CF) for learned electroencephalogram(EE...
Epilepsy Seizures Signal Processing, Computer-Assisted Machine Learning Algorithms Electroencephalography Humans
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Machine learning allows expert level classification of intraoperative motor evoked potentials during neurosurgical procedures.

Computers in biology and medicine Aug 21, 2024
OBJECTIVE: To develop and evaluate machine learning (ML) approaches for muscle identification using intraoperative motor evoked potentials (MEPs), and to compare their performance to human experts.
Female Signal Processing, Computer-Assisted Adult Male Neurosurgical Procedures Humans Middle Aged Evoked Potentials, Motor Machine Learning Intraoperative Neurophysiological Monitoring
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Non-Intrusive System for Honeybee Recognition Based on Audio Signals and Maximum Likelihood Classification by Autoencoder.

Sensors (Basel, Switzerland) Aug 21, 2024
Artificial intelligence and Internet of Things are playing an increasingly important role in monitoring beehives. In this paper, we propose a method for automatic recognition of honeybee type by analyzing the sound generated by worker bees and drone ...
Signal Processing, Computer-Assisted Bees Neural Networks, Computer Likelihood Functions Artificial Intelligence Algorithms Animals
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Subject-independent auditory spatial attention detection based on brain topology modeling and feature distribution alignment.

Hearing research Aug 14, 2024
Auditory spatial attention detection (ASAD) seeks to determine which speaker in a surround sound field a listener is focusing on based on the one's brain biosignals. Although existing studies have achieved ASAD from a single-trial electroencephalogra...
Attention Humans Models, Neurological Brain Waves Auditory Perception Acoustic Stimulation Neural Networks, Computer Electroencephalography Sound Localization Auditory Pathways Brain Signal Processing, Computer-Assisted
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Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

Journal of neuroscience methods Aug 14, 2024
BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing m...
Movement Electrocorticography Epilepsy Signal Processing, Computer-Assisted Fingers Humans Neural Networks, Computer Machine Learning Adult Male Female Young Adult
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Automatic detection of cardiac conditions from photos of electrocardiogram captured by smartphones.

Heart (British Cardiac Society) Aug 14, 2024
BACKGROUND: Researchers have developed machine learning-based ECG diagnostic algorithms that match or even surpass cardiologist level of performance. However, most of them cannot be used in real-world, as older generation ECG machines do not permit i...
Humans Machine Learning Algorithms Signal Processing, Computer-Assisted Arrhythmias, Cardiac Heart Rate Smartphone Photography Mobile Applications Electrocardiography
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Artificial intelligence-driven electrocardiography: Innovations in hypertrophic cardiomyopathy management.

Trends in cardiovascular medicine Aug 13, 2024
Hypertrophic Cardiomyopathy (HCM) presents a complex diagnostic and prognostic challenge due to its heterogeneous phenotype and clinical course. Artificial Intelligence (AI) and Machine Learning (ML) techniques hold promise in transforming the role o...
Humans Risk Factors Risk Assessment Diagnosis, Computer-Assisted Deep Learning Artificial Intelligence Prognosis Clinical Decision-Making Signal Processing, Computer-Assisted Death, Sudden, Cardiac Heart Rate Cardiomyopathy, Hypertrophic Electrocardiography Action Potentials Predictive Value of Tests
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Enhanced Hand Gesture Recognition with Surface Electromyogram and Machine Learning.

Sensors (Basel, Switzerland) Aug 13, 2024
This study delves into decoding hand gestures using surface electromyography (EMG) signals collected via a precision Myo-armband sensor, leveraging machine learning algorithms. The research entails rigorous data preprocessing to extract features and ...
Electromyography Pattern Recognition, Automated Movement Gestures Signal Processing, Computer-Assisted Hand Female Young Adult Humans Adult Machine Learning Male Algorithms
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Age prediction from 12-lead electrocardiograms using deep learning: a comparison of four models on a contemporary, freely available dataset.

Physiological measurement Aug 12, 2024
The 12-lead electrocardiogram (ECG) is routine in clinical use and deep learning approaches have been shown to have the identify features not immediately apparent to human interpreters including age and sex. Several models have been published but no ...
Signal Processing, Computer-Assisted Middle Aged Deep Learning Electrocardiography Humans Female Aged Young Adult Adult Male
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