A comparative study of four novel sleep apnoea episode prediction systems

The prediction of sleep apnoea and hypopnoea episodes could allow treatment to be applied before the event be-comes detrimental to the patients sleep, and for a more spe-cific form of treatment. It is proposed that features extracted from breaths preceding an apnoea and hypopnoea could be used in neural networks for the prediction of these events. Four different predictive systems were created, processing the nasal airflow signal using epoching, the inspiratory peak and expiratory trough values, principal component analysis (PCA) and empirical mode decomposition (EMD). The neu-ral networks were validated with naïve data from six over-night polysomnographic records, resulting in 83.50% sensi-tivity and 90.50% specificity. Reliable prediction of apnoea and hypopnoea is possible using the epoched flow and EMD of breaths preceding the event

Overview of optical BCI research at NUI Maynooth

A brain-computer interface (BCI) is a device that provides a user with an alternative means of interactive communication, rather than the usual modes via physical gestures/speech. Thus it acts as a neural prosthesis bypassing the normal output pathways of the brain, i.e. spinal cord and periphery cascade. An optical BCI uses optical means of determining the user's mental intent, e.g. to turn on a light switch, by spectroscopic analysis of the intact brain

Overview of optical BCI research at NUI Maynooth

A brain-computer interface (BCI) is a device that provides a user with an alternative means of interactive communication, rather than the usual modes via physical gestures/speech. Thus it acts as a neural prosthesis bypassing the normal output pathways of the brain, i.e. spinal cord and periphery cascade. An optical BCI uses optical means of determining the user's mental intent, e.g. to turn on a light switch, by spectroscopic analysis of the intact brain

Perceptual Centre correlates in Evoked Potentials

Perceptual centres (p-centres) are the subjective moments of occurrence of acoustic stimuli. When sounds are perceived in synchrony or are regularly spaced, it is their p-centres which occur synchronously or are isochronous. In order to analyse or model the acoustic features which influence the p-centre, it is necessary to measure p-centres for many stimuli. However there is a problem: it is difficult for an external observer to determine the exact time at which a listener perceives a sound’s occurrence. A possible solution is to find a measurable electrophysiological correlate of the p-centre. In order to investigate this, an experiment is described which compares features of the Auditory Evoked Potential (AEP) response and p-centres for a number of speech and synthetic stimuli. The results indicate a correlation between the latency of the dominant negative peak of the AEP and the p-centre

A joint coregistration of rotated multitemporal SAR images based on the cross-cross-correlation

Accurate synthetic aperture radar (SAR) images coregistration is on the base of several remote sensing applications, such as interferometry, change detection, etc. This paper proposes a new algorithm for jointly coregister a stack of multitemporal SAR images exploiting the cross-correlations computed for each couple of patches' cross-correlation. By doing so, the method is capable of exploit also the respective misregistration information between the slave during the estimation process. This methodology is applied to improve the performance of the constrained Least Squares (CLS) optimization method that does not account for the reciprocal information related to the slaves. Tests on real-recorded data shown the benefits of the proposed method in terms of root mean square error (RMSE) for images affected by respective rotations

Biophotonic Methods for Brain-Computer Interfaces

Poste

Steady State Visual Stimulation of the Brain: Optical Study of Task Related Effects

Near-infrared (NIR) and electroencephalography (EEG) systems were applied simultaneously to check a possibility of an optical brain-computer interface (BCI) based on visual protocol. A two-wavelength, two-channel NIR system using lock-in amplifiers to filter received signal was designed for monitoring of light absorption. An improved single photon-counting system based on NIR laser diodes and multichannel scaling was configured for fast one-wavelength capturing of the scatter changes in the area of the human brain corresponding to the task. Designed protocols consisted of the pattern reversed repeatedly at various frequencies. The stimulus repetition improves processing according to some behavioural measure as e.g. greater accuracy in identifying the stimulus or faster response times to make a decision about it, and often occurs under the same experimental conditions. Under certain conditions rather increased activity in the brain could be observed which results in a longer habituation time. Results of tests are presented in current article

A 12-Channel, real-time near-infrared spectroscopy instrument for brain-computer interface applications

A continuous wave near-infrared spectroscopy (NIRS) instrument for brain-computer interface (BCI) applications is presented. In the literature, experiments have been carried out on subjects with such motor degenerative diseases as amyotrophic lateral sclerosis, which have demonstrated the suitability of NIRS to access intentional functional activity, which could be used in a BCI as a communication aid. Specifically, a real-time, multiple channel NIRS tool is needed to realise access to even a few different mental states, for reasonable baud rates. The 12-channel instrument described here has a spatial resolution of 30mm, employing a flexible software demodulation scheme. Temporal resolution of ~100ms is maintained since typical topographic imaging is not needed, since we are only interested in exploiting the vascular response for BCI control. A simple experiment demonstrates the ability of the system to report on haemodynamics during single trial mental arithmetic tasks. Multiple trial averaging is not required

Combining interpolation and 3D level set method (I+3DLSM) for medical image segmentation

A combined interpolation - 3D Level Set Method (I+3DLSM) based segmentation process is presented. The performance in terms of accuracy of the 3-dimensional (3D) level set method (LSM) in the segmentation of throat regions from highly anisotropic magnetic resonance imaging (MRI) volumes, with and without an interpolation step is evaluated. Qualitative and quantitative results from real MRI data suggest that performing interpolation, to reconstruct isotropic MRI volumes, prior to 3D LSM improves the accuracy of the segmentation results, compared to interpolation post 3D LSM and no interpolation at all