Search results for " recognition"
showing 10 items of 3220 documents
Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks
2019
Deep learning has contributed greatly to functional magnetic resonance imaging (fMRI) analysis, however, spatial maps derived from fMRI data by independent component analysis (ICA), as promising biomarkers, have rarely been directly used to perform individualized diagnosis. As such, this study proposes a novel framework combining ICA and convolutional neural network (CNN) for classifying schizophrenia patients (SZs) and healthy controls (HCs). ICA is first used to obtain components of interest which have been previously implicated in schizophrenia. Functionally informative slices of these components are then selected and labelled. CNN is finally employed to learn hierarchical diagnostic fea…
Increasing Stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition
2018
Tensor decomposition has been widely employed for EEG signal processing in recent years. Constrained and regularized tensor decomposition often attains more meaningful and interpretable results. In this study, we applied sparse nonnegative CANDECOMP/PARAFAC tensor decomposition to ongoing EEG data under naturalistic music stimulus. Interesting temporal, spectral and spatial components highly related with music features were extracted. We explored the ongoing EEG decomposition results and properties in a wide range of sparsity levels, and proposed a paradigm to select reasonable sparsity regularization parameters. The stability of interesting components extraction from fourteen subjects’ dat…
Functional Near Infrared Spectroscopy System Validation for Simultaneous EEG-FNIRS Measurements
2019
Functional near-infrared spectroscopy (fNIRS) applied to brain monitoring has been gaining increasing relevance in the last years due to its not invasive nature and the capability to work in combination with other well–known techniques such as the EEG. The possible use cases span from neural-rehabilitation to early diagnosis of some neural diseases. In this work a wireline FPGA–based fNIRS system, that use SiPM sensors and dual-wavelength LED sources, has been designed and validated to work with a commercial EEG machine without reciprocal interference.
Empirical Mode Decomposition on Mismatch Negativity
2008
Empirical mode decomposition (EMD) has been applied in the various disciplines to extract the desired signal. The basic principle is to decompose a time series into intrinsic mode functions (IFMs) and each IFM corresponds to an oscillation phenomenon. A statistical description of the oscillatory activities of the EEG has been well known. It is desired to extract single oscillatory process from the EEG by EMD. Mismatch negativity (MMN) can be automatically elicited by the deviant stimulus in an oddball paradigm, in which physically the deviant stimulus occurs among repetitive and homogeneous stimuli. MMN thus reflects the ability of the brain to detect changes in auditory stimuli. So, the MM…
Extract Mismatch Negativity and P3a through Two-Dimensional Nonnegative Decomposition on Time-Frequency Represented Event-Related Potentials
2010
This study compares the row-wise unfolding nonnegative tensor factorization (NTF) and the standard nonnegative matrix factorization (NMF) in extracting time-frequency represented event-related potentials—mismatch negativity (MMN) and P3a from EEG under the two-dimensional decomposition The criterion to judge performance of NMF and NTF is based on psychology knowledge of MMN and P3a MMN is elicited by an oddball paradigm and may be proportionally modulated by the attention So, participants are usually instructed to ignore the stimuli However the deviant stimulus inevitably attracts some attention of the participant towards the stimuli Thus, P3a often follows MMN As a result, if P3a was large…
Effectiveness of tDCS at Improving Recognition and Reducing False Memories in Older Adults
2021
Background: False memories tend to increase in healthy and pathological aging, and their reduction could be useful in improving cognitive functioning. The objective of this study was to use an active–placebo method to verify whether the application of transcranial direct current stimulation (tDCS) improved true recognition and reduced false memories in healthy older people. Method: Participants were 29 healthy older adults (65–78 years old) that were assigned to either an active or a placebo group
Ocular counterrolling. Some practical considerations of a new evaluation method for diagnostic purposes.
1986
Ocular counterrolling (OCR) data taken from the literature (12 publications) were used to test the best fit (least-square fit) of these measurements with respect to three mathematical models: a sine relation between OCR and the lateral tilt stimulus, a complex cosine-square relation, and a logarithmic relation between OCR gain and tilt. The latter proved to be the best fitting function. On the basis of this model, we attempted to define a physiological transfer function between OCR gain and tilt, which could serve as a reference of normal population, assuming healthy subjects for the investigations applied. Comparison of this physiological range with pathological data demonstrated marked di…
Primary ciliary dyskinesia assessment by means of optical flow analysis of phase-contrast microscopy images
2014
Primary ciliary dyskinesia implies cilia with defective or total absence of motility, which may result in sinusitis, chronic bronchitis, bronchiectasis and male infertility. Diagnosis can be difficult and is based on an abnormal ciliary beat frequency (CBF) and beat pattern. In this paper, we present a method to determine CBF of isolated cells through the analysis of phase-contrast microscopy images, estimating cilia motion by means of an optical flow algorithm. After having analyzed 28 image sequences (14 with a normal beat pattern and 14 with a dyskinetic pattern), the normal group presented a CBF of 5.2 +/- 1.6 Hz, while the dyskinetic patients presented a 1.9 +/- 0.9 Hz CBF. The cutoff …
A Multi-Variate Predictability Framework to Assess Invasive Cardiac Activity and Interactions during Atrial Fibrillation
2017
Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conc…
Laser illumination designs for snapshot multi-spectral-line imaging
2019
For multi-spectral imaging, both acquisition time of the spectral image set and the spectral bandwidth of each image have to be minimized. Ultimate performance can be achieved if the set of monochromatic (single-wavelength) spectral images is obtained with a single snapshot — a technique provisionally called "snapshot multi-spectral-line imaging" or SMSLI. Using contemporary RGB colour cameras, up to three spectral line images can be extracted from a snapshot image data cube at specific illumination that comprises only three spectral lines, each of them positioned within one of the detection bands (R, G or B) [1]. Techniques able to provide more spectral line images are under development, a…