AIMC Topic: Signal Processing, Computer-Assisted

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Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals.

IEEE transactions on bio-medical engineering
OBJECTIVE: An autoencoder-based framework that simultaneously reconstruct and classify biomedical signals is proposed. Previous work has treated reconstruction and classification as separate problems. This is the first study that proposes a combined ...

Predicting the physiological response of Tivela stultorum hearts with digoxin from cardiac parameters using artificial neural networks.

Bio Systems
Multi-layer perceptron artificial neural networks (MLP-ANNs) were used to predict the concentration of digoxin needed to obtain a cardio-activity of specific biophysical parameters in Tivela stultorum hearts. The inputs of the neural networks were th...

The extraction of motion-onset VEP BCI features based on deep learning and compressed sensing.

Journal of neuroscience methods
BACKGROUND: Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong back...

An efficient automatic workload estimation method based on electrodermal activity using pattern classifier combinations.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Automatic workload estimation has received much attention because of its application in error prevention, diagnosis, and treatment of neural system impairment. The development of a simple but reliable method using minimum number of psychophysiologica...

Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Speech signal processing techniques have provided several contributions to pathologic voice identification, in which healthy and unhealthy voice samples are evaluated. A less common approach is to identify laryngeal pathologies, for which...

Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the S...

Beatquency domain and machine learning improve prediction of cardiovascular death after acute coronary syndrome.

Scientific reports
Frequency domain measures of heart rate variability (HRV) are associated with adverse events after a myocardial infarction. However, patterns in the traditional frequency domain (measured in Hz, or cycles per second) may capture different cardiac phe...

Correlated EEG Signals Simulation Based on Artificial Neural Networks.

International journal of neural systems
In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed metho...

A novel machine learning-enabled framework for instantaneous heart rate monitoring from motion-artifact-corrupted electrocardiogram signals.

Physiological measurement
This paper proposes a novel machine learning-enabled framework to robustly monitor the instantaneous heart rate (IHR) from wrist-electrocardiography (ECG) signals continuously and heavily corrupted by random motion artifacts in wearable applications....

Fault Diagnosis for Analog Circuits by Using EEMD, Relative Entropy, and ELM.

Computational intelligence and neuroscience
This paper presents a novel fault diagnosis method for analog circuits using ensemble empirical mode decomposition (EEMD), relative entropy, and extreme learning machine (ELM). First, nominal and faulty response waveforms of a circuit are measured, r...