Search results for "Wavelet analysis"
showing 6 items of 26 documents
Regular theta-firing neurons in the nucleus incertus during sustained hippocampal activation
2015
This paper describes the existence of theta-coupled neuronal activity in the nucleus incertus (NI). Theta rhythm is relevant for cognitive processes such as spatial navigation and memory processing, and can be recorded in a number of structures related to the hippocampal activation including the NI. Strong evidence supports the role of this tegmental nucleus in neural circuits integrating behavioural activation with the hippocampal theta rhythm. Theta oscillations have been recorded in the local field potential of the NI, highly coupled to the hippocampal waves, although no rhythmical activity has been reported in neurons of this nucleus. The present work analyses the neuronal activity in t…
ERG signal analysis using wavelet transform
2009
The wavelet analysis is a powerful tool for analyzing and detecting features of signals characterized by time-dependent statistical properties, as biomedical signals. The identification and the analysis of the components of these signals in the time-frequency domain, give meaningful information about the physiological mechanisms that govern them. This article presents the results of the wavelet analysis applied to the a-wave component of the human electroretinogram. In order to deepen and improve our knowledge about the behavior of the early photoreceptoral response, including the possible activation of interactions and correlations among the photoreceptors, we have detected and identified …
An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals
2022
Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for psychiatrists while examining patients, and for neuromarketing applications. Multimodal signals for emotion charting include electrocardiogram (ECG) signals, electroencephalogram (EEG) signals, and galvanic skin response (GSR) signals. EEG, ECG, and GSR are also known as physiological signals, which can be used for identification of human emotions. Due to the unbiased nature of physiological signals, this field has become a great motivation in recent research as physiological signals are generated autonomously from human central nervous system. Researchers have developed multiple methods for …
The Decline in U.S. Output Growth Volatility: A Wavelet Analysis
2013
The aim of the paper is to determine whether or not the volatility of the growth rate of US output has changed in the period since late 1940's, and to attribute a precise date, if possible, to any such change. By applying the Discrete Wavelet Transform (DWT) to the annualized quarter-to quarter output growth series, we can test the homogeneity of the variance on a scale by scale basis without needing to fit a parametric model to the observed time series. A version of the Inclan and Tiao (1994) Normalised and Centered Cumulative Sum of Squares test, adapted to wavelet analysis, leads us to reject the null hypothesis of constant variance in the two levels of decomposition of the highest resol…
Contribution to the design of a smart electromyostimulator
2013
This project aims to develop a new tool for neuromuscular reeducation. Its function is to improve the quality and the duration of muscular strengthening training sessions and training of motor function for patients suffering from muscle deconditioning. A "smart" electromyostimulator using, at the same time, techniques of electrostimulation (EMS) and analysis of electromyography (EMG) allows the control in real time electrical stimulation parameters considering the physiological fatigue of the stimulated muscle. This control, performed on stimulation parameters depending on electrical response of muscles (M wave), allows the muscle stimulation taking into account the muscular reaction to the…
Voluntary and Involuntary Attention in Bistable Visual Perception: A MEG Study
2020
In this study, voluntary and involuntary visual attention focused on different interpretations of a bistable image, were investigated using magnetoencephalography (MEG). A Necker cube with sinusoidally modulated pixels' intensity in the front and rear faces with frequencies 6.67 Hz (60/9) and 8.57 Hz (60/7), respectively, was presented to 12 healthy volunteers, who interpreted the cube as either left- or right-oriented. The tags of these frequencies and their second harmonics were identified in the average Fourier spectra of the MEG data recorded from the visual cortex. In the first part of the experiment, the subjects were asked to voluntarily control their attention by interpreting the cu…