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The domain specific nature of biosignal storage formats, along with the lack of support for metadata in general purpose biosignal libraries, has hampered the easy interchange of biosignals between disciplines and their integration with physiological modelling software. Extensible Biosignal Metadata (XBM) is introduced as a standard framework to facilitate the sharing of information between and within...
This work presents a multi-channel patient-independent neonatal seizure detection system based on the SVM classifier. Several post-processing steps are proposed to increase temporal precision and robustness of the system and their influence on performance is shown. The SVM-based system is evaluated on a large clinical dataset using several epoch-based and event based metrics and curves of performance...
Robustness in signal processing is crucial for the purpose of reliably interpreting physiological features from noisy data in biomedical applications. We present a robust algorithm based on the reformulation of a well-known spatial filtering and feature extraction algorithm named Common Spatial Patterns (CSP). We cast the problem of learning CSP into a probabilistic framework, which allows us to gain...
Different types of analyses of scalp and intracranial electroencephalography (EEG) recordings using linear and nonlinear time series analysis method have been done. They showed strong evidence of detectable changes in the EEG dynamics from minutes up to several hours in advance of seizure onset. The predictive performance of univariate and bivariate measures, comprising both linear and non-linear...
In this paper, we present a fuzzy rule-based system for the automatic detection of seizures in the intracranial EEG (IEEG) recordings. A total of 302.7 hours of the IEEG with 78 seizures, recorded from 21 patients aged between 10 and 47 years were used for the evaluation of the system. After preprocessing, temporal, spectral, and complexity features were extracted from the segmented IEEGs. The results...
Different control strategies exist for use in a brain-computer interface (BCI). Although process control is the prevailing control strategy for most sensorimotor rhythm based BCIs, the goal selection strategy more closely resembles normal motor control and may be more accurate, faster to use, and easier to learn. We describe here a sensorimotor rhythm based goal selection BCI and a pilot study to...
Intra-cranial electroencephalograms (EEG) from two patients diagnosed with epilepsy are sampled at 1 kHz, enabling analysis and feature extraction at frequency bands above the gamma range. This study focuses on the extraction of linear features (including autoregressive, autoregressive-moving average and Fourier coefficients) obtained at both low (below 100 Hz) and high (100-500 Hz) bands of the signal...
In the present study, we utilize methods from graph theory to analyze epileptogenic network properties during periods of ictal activity. Using these methods, we analyzed the DTF-based causal information flow in nine seizures recorded from two patients undergoing presurgical monitoring for the treatment of medically intractable epilepsy. From the results, we observed a high degree of correlation between...
The falling asleep period is the shift from the waking stage to sleep stages 1 and 2. Changes during the falling asleep period can be observed on electroencephalograms (EEGs). In this research, we developed a technique for estimating sleep stage at the falling asleep period without using EEGs. We performed a Lorenz plot (LP) using the intervals between heartbeats, known as electrocardiogram (ECG)...
Patterns in electroencephalogram (EEG) signals are analyzed for a brain computer interface (BCI). An important aspect of this analysis is the work on transformations of high dimensional EEG data to low dimensional spaces in which we can classify the data according to mental tasks being performed. In this research we investigate how a neural network (NN) in an auto-encoder with bottleneck configuration...
The majority of Brain Computer Interfaces have relied on signals related to primary motor cortex and the operation of the contralateral limb. Recently, the physiology associated with same-sided (ipsilateral) motor movements has been found to have a unique cortical physiology. This study sets out to assess whether more complex motor movements can be discerned utilizing ipsilateral cortical signals...
A growing number of brain monitoring tools for medical and biomedical applications such as surgery have been developed. Although many assistive technologies (e.g., brain computer interface (BCI) systems) aiming to restore cognitive-motor deficits are under development, no functional neural indicator or brain biomarker able to track the cortical dynamics of the brain when interacting with new tools...
The goal of this study was to experimentally investigate the influence of the white matter (WM) anisotropy on the EEG source localization. We acquired both visual evoked potential (VEP) and functional MRI (fMRI) data from three human subjects presented with identical visual stimuli. A finite element method (FEM) head model with or without incorporating the WM anisotropy was built to solve the EEG...
Behavioural microsleeps (BMs) are brief episodes of absent responsiveness accompanied by slow-eye-closure. They frequently occur as a consequence of sleep-deprivation, an extended monotonous task, and are modulated by the circadian rhythm and sleep homeostatic pressure. In this paper, a multimodal method to investigate the neural correlates of BMs using simultaneous recording of fMRI, eye-video, VEOG,...
To characterize transition periods of entrance to and emergence from anesthetic-induced unconsciousness in terms of thalamocortical neural activity, we devised a new method estimating a transition point of anesthetic-induced loss of consciousness. The method continuously monitors an animal's head motion in response to forced movement on treadmill and uses the motion signals as a criterion of the transition...
As the average life expectancy increases, particularly in developing countries, prevalence of neurodegenerative diseases has also increased. This trend is especially alarming for Alzheimer's disease (AD); as there is no cure to stop or reverse the effects of AD. However, recent pharmacological advances can slow the progression of AD, but only if AD is diagnosed at early stages. We have previously...
A simple algorithm to automatically detect segments with epileptic seizures in long EEG records has been developed. The main advantages of the proposed method are: the simple algorithm used and the lower computational cost. The algorithm measures the energy of each EEG channel by a sliding window and calculates some features of each patient signal to detect the epileptic seizure. It is also able to...
Cross-modality is the development of cross link between the modalities in the brain following sensory deprivation in the early stage. Cross modality analysis was previously done with fMRI, MEG and PET images for studying the changes in cerebral activities. Instead of these imaging techniques, this work involves in deriving self similarity parameter using detrended fluctuation analysis of EEG from...
The capacity to decode kinematics of intended movement from neural activity is necessary for the development of neuromotor prostheses such as smart artificial arms. Thus far, most of the progress in the development of neuromotor prostheses has been achieved by decoding kinematics of the hand from intracranial neural activity. The comparatively low signal-to-noise ratio and spatial resolution of neural...
Sleep apnoea is a sleep breathing disorder which causes changes in cardiac and neuronal activity and discontinuities in sleep pattern when observed via electrocardiogram (ECG) and electroencephalogram (EEG). This paper presents a pilot study result of assessing the correlation between EEG frequency bands and ECG heart rate variability (HRV) in normal and sleep apnoea human clinical patients at different...
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