AIMC Topic: Signal Processing, Computer-Assisted

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Support vector machine and fuzzy C-mean clustering-based comparative evaluation of changes in motor cortex electroencephalogram under chronic alcoholism.

Medical & biological engineering & computing
In this study, the magnitude and spatial distribution of frequency spectrum in the resting electroencephalogram (EEG) were examined to address the problem of detecting alcoholism in the cerebral motor cortex. The EEG signals were recorded from chroni...

A robust computational technique for model order reduction of two-time-scale discrete systems via genetic algorithms.

Computational intelligence and neuroscience
A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbati...

Traffic speed data imputation method based on tensor completion.

Computational intelligence and neuroscience
Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel...

RSTFC: A Novel Algorithm for Spatio-Temporal Filtering and Classification of Single-Trial EEG.

IEEE transactions on neural networks and learning systems
Learning optimal spatio-temporal filters is a key to feature extraction for single-trial electroencephalogram (EEG) classification. The challenges are controlling the complexity of the learning algorithm so as to alleviate the curse of dimensionality...

Multiple actor-critic structures for continuous-time optimal control using input-output data.

IEEE transactions on neural networks and learning systems
In industrial process control, there may be multiple performance objectives, depending on salient features of the input-output data. Aiming at this situation, this paper proposes multiple actor-critic structures to obtain the optimal control via inpu...

A Comparison of SVM and GMM-Based Classifier Configurations for Diagnostic Classification of Pulmonary Sounds.

IEEE transactions on bio-medical engineering
GOAL: The aim of this study is to find a useful methodology to classify multiple distinct pulmonary conditions including the healthy condition and various pathological types, using pulmonary sounds data.

Multi-motion robots control based on bioelectric signals from single-channel dry electrode.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This article presents a multi-motion control system to help severe disabled people operate an auxiliary appliance using neck-up bioelectric signals measured by a single-channel dry electrode on the forehead. The single-channel dry-electrode multi-mot...

Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters.

IEEE transactions on bio-medical engineering
Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need...

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

Journal of clinical monitoring and computing
Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of ...