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In this paper, we have developed 40 channel multiple electrodes mounted on the surface of mouse's skull using polyimide substrate and tested its performance by measuring EEG signals. The recording site of the electrode was electroplated by Pt to enhance both contact impedance and adhesive strength by applying proper current, cleaning surface and removing H2 gas bubbles. For in vivo test, the electrode...
This study aims to explore whether human intentions to move or cease to move right and left hands can provide four spatiotemporal patterns in single-trial non-invasive EEG signals to achieve a two-dimensional cursor control. Subjects performed motor tasks by either physical movement or motor imagery. Spatial filtering, temporal filtering, feature selection and classification methods were explored...
We propose a partial directed coherence (PCD) method based on a sparse multivariate autoregressive (mAR) model to investigate patterns of information flow in electroencephalography (EEG) recordings in Parkinson's disease (PD) patients performing a visually-guided motor task. The use of a sparsity constraint on the mAR matrix addresses issues such as sample size, model order selection and number of...
Recent research efforts in studying brain connectivity has provided new perspectives to understanding of neurophysiology of brain function. Connectivity measures are typically computed from electroencephalogram (EEG) signals, yet the presence of volume conduction makes interpretation of results difficult. One possible alternative is to model the connectivity in the source space. In this study, we...
This paper focuses on the problem of how time-frequency representation influences the generalization ability of the `synthesized time-frequency spatial pattern (TFSP)' algorithm in brain computer interface (BCI) for classification. TFSP methods use time-frequency analysis to extract features in both time and frequency domains. Different time-frequency analysis methods have been used before. However,...
The brain-to-skull conductivity ratio (BSCR) is an important parameter in EEG source imaging and localization. Misspecification of this value may introduce localization errors in the estimation of brain electrical activity. However, the effect of this ratio has not been well understood despite many investigations. In the present study, we conducted a series of computer simulations to investigate the...
We introduce a subspace learning approach for multi-channel Local Field Potentials (LFP), and demonstrate its application in movement direction decoding for 8 directions movement. We show that the subspace learning method can effectively address the issue of signal instability across recording sessions by extracting recurrent features from the data. We present results for movement direction decoding,...
Implicit Wiener series are a powerful tool to build Volterra representations of time series with any degree of non-linearity. A natural question is then whether higher order representations yield more useful models. In this work we shall study this question for ECoG data channel relationships in epileptic seizure recordings, considering whether quadratic representations yield more accurate classifiers...
The brain is a complex biological system with dynamic interactions between its sub-systems. One particular challenge in the study of this complex system is the identification of dynamic functional networks underlying observed neural activity. Current imaging approaches index local neural activity very well, but there is an increasing need for methods that quantify the interaction between regional...
Sleep recording is the quantitative method used in sleep centers in order to assess sleep disorders and to quantify pathological events occurring during sleep. Cardiorespiratory polysomnography is the method used for sleep recording. Standards for sleep recording stem back to 1968 and were compiled by Rechtschaffen and Kales with specifications for recording and analysis of the sleep EEG. An update...
The filter bank common spatial pattern (FBCSP) algorithm performs autonomous selection of key temporal-spatial discriminative EEG characteristics in motor imagery-based brain computer interfaces (MI-BCI). However, FBCSP is sensitive to outliers because it involves multiple estimations of covariance matrices from EEG measurements. This paper proposes a Robust FBCSP (RFBCSP) algorithm whereby the estimates...
This paper describes a new approach in features extraction using time-frequency distributions (TFDs) for detecting epileptic seizures to identify abnormalities in electroencephalogram (EEG). Particularly, the method extracts features using the smoothed pseudo Wigner-Ville distribution combined with the McAulay-Quatieri sinusoidal model and identifies abnormal neural discharges. We propose a new feature...
This paper investigates the classification of multi-class motor imagery for electroencephalogram (EEG)-based Brain-Computer Interface (BCI) using the Filter Bank Common Spatial Pattern (FBCSP) algorithm. The FBCSP algorithm classifies EEG measurements from features constructed using subject-specific temporal-spatial filters. However, the FBCSP algorithm is limited to binary-class motor imagery. Hence,...
In this paper we present further results of our asynchronous and non-invasive BMI for the continuous control of an intelligent wheelchair. Three subjects participated in two experiments where they steered the wheelchair spontaneously, without any external cue. To do so the users learn to voluntary modulate EEG oscillatory rhythms by executing three mental tasks (i.e., mental imagery) that are associated...
Evaluation of synchronization between signals can give new insights into the functioning of the related systems. Methods that can detect synchronization or coupling between signals can be divided two types: linear and non linear methods. In this paper we use the non linear correlation coefficient (h2) to show the difference in synchronization between efficient uterine contractions during labor and...
For as many as 30% of epilepsy patients, seizures are poorly controlled with medication alone. For some of these patients surgery may be an option: the brain region responsible for seizure onset may be removed surgically. However, this requires accurate delineation of the seizure onset region. Currently, the key to making this determination is seizure EEG. Therefore, EEG recordings must continue until...
The common spatial patterns (CSP) algorithm is commonly used to extract discriminative spatial filters for the classification of electroencephalogram (EEG) signals in the context of brain-computer interfaces (BCIs). However, CSP is based on a sample-based covariance matrix estimation. Therefore, its performance is limited when the number of available training samples is small. In this paper, the CSP...
In this study we investigated the existence and the nature of rhythmic changes in EEG associated with ventilatory oscillations in heart failure (HF) patients with periodic breathing (PB). Since nonlinear mechanisms are thought to be involved in the generation of EEG, we hypothesized that a mathematical approach based on nonlinear methods would provide relevant information on the association between...
The aim of this paper is to investigate the possibility of using empirical mode decomposition (EMD) method in detecting the desynchronized mu rhythm of motor imagery EEG signal. A number of EEG studies have indentified the mu rhythm desynchronization a reliable EEG pattern for brain-computer interface. Considering the non-stationary characteristics of the motor imagery EEG, the EMD method is proposed...
Stroke has been one of the leading causes of mortality and long-term morbidity around the world. Describing the cortical synchrony has been useful in understanding of central nervous system disorders after brain injury. In this paper, we investigated the large scale cortical phase synchronization derived from multichannel electroencephalogram (EEG) recordings of bilateral ischemic stroke patients(n...
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