AIMC Topic: Signal Processing, Computer-Assisted

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Relevant Feature Selection from a Combination of Spectral-Temporal and Spatial Features for Classification of Motor Imagery EEG.

Journal of medical systems
This paper presents a novel algorithm (CVSTSCSP) for determining discriminative features from an optimal combination of temporal, spectral and spatial information for motor imagery brain computer interfaces. The proposed method involves four phases. ...

The design and validation of a hybrid digital-signal-processing plug-in for traditional cochlear implant speech processors.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cochlear implants (CIs) are electronic devices restoring partial hearing to deaf individuals with profound hearing loss. In this paper, a new plug-in for traditional IIR filter-banks (FBs) is presented for cochlear implants ...

ANN and Fuzzy Logic Based Model to Evaluate Huntington Disease Symptoms.

Journal of healthcare engineering
We introduce an approach to predict deterioration of reaction state for people having neurological movement disorders such as hand tremors and nonvoluntary movements. These involuntary motor features are closely related to the symptoms occurring in p...

Detecting Vascular Age Using the Analysis of Peripheral Pulse.

IEEE transactions on bio-medical engineering
UNLABELLED: Vascular ageing is known to be accompanied by arterial stiffening and vascular endothelial dysfunction, and represents an independent factor contributing to the development of cardiovascular disease. The microvascular pulse is affected by...

Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful application of these methods in motor imagery (MI) brain-compu...

Multichannel lung sound analysis for asthma detection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Lung sound signals convey valuable information of the lung status. Auscultation is an effective technique to appreciate the condition of the respiratory system using lung sound signals. The prior works on asthma detection fr...

Bat detective-Deep learning tools for bat acoustic signal detection.

PLoS computational biology
Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open s...

Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals.

PloS one
Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free B...

Multiple Instance Dictionary Learning for Beat-to-Beat Heart Rate Monitoring From Ballistocardiograms.

IEEE transactions on bio-medical engineering
A multiple instance dictionary learning approach, dictionary learning using functions of multiple instances (DL-FUMI), is used to perform beat-to-beat heart rate estimation and to characterize heartbeat signatures from ballistocardiogram (BCG) signal...

T-wave end detection using neural networks and Support Vector Machines.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: In this paper we propose a new approach for detecting the end of the T-wave in the electrocardiogram (ECG) using Neural Networks and Support Vector Machines.