AIMC Topic: Signal Processing, Computer-Assisted

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Viscosity Prediction in a Physiologically Controlled Ventricular Assist Device.

IEEE transactions on bio-medical engineering
OBJECTIVE: We present a novel machine learning model to accurately predict the blood-analog viscosity during support of a pathological circulation with a rotary ventricular assist device (VAD). The aim is the continuous monitoring of the hematocrit (...

Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG.

Computational intelligence and neuroscience
Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recogn...

A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification.

Computational and mathematical methods in medicine
Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on diffe...

Max-margin weight learning for medical knowledge network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The application of medical knowledge strongly affects the performance of intelligent diagnosis, and method of learning the weights of medical knowledge plays a substantial role in probabilistic graphical models (PGMs). The p...

Random ensemble learning for EEG classification.

Artificial intelligence in medicine
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rap...

Application of stacked convolutional and long short-term memory network for accurate identification of CAD ECG signals.

Computers in biology and medicine
Coronary artery disease (CAD) is the most common cause of heart disease globally. This is because there is no symptom exhibited in its initial phase until the disease progresses to an advanced stage. The electrocardiogram (ECG) is a widely accessible...

Non-water-suppressed H FID-MRSI at 3T and 9.4T.

Magnetic resonance in medicine
PURPOSE: This study investigates metabolite concentrations using metabolite-cycled H free induction decay (FID) magnetic resonance spectroscopic imaging (MRSI) at ultra-high fields.

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification.

International journal of neural systems
The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the ...

Epileptic seizure detection in EEG signal using machine learning techniques.

Australasian physical & engineering sciences in medicine
Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are ti...