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Tripolar concentric ring electrode (TCRE) sensors have unique properties. These sensors have been used to acquire various bio-signals such as: electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG). Compared to conventional disc electrode signals TCRE EEG (tEEG) has four times better signal-to-noise ratio, eleven times better mutual information and spatial resolution....
In this paper, we present an efficient approach to investigate data of EEG-based Brain-Machine Interface (BMI) using a bagging Support Vector Machines (SVMs) for collected data classification from a P3-speller paradigm. The combination of SVMs allows to handle the problem of EEG data variability between the different sessions of the acquisition process. This variability is caused by temporal non-stationarity...
Electrocorticographic (ECoG) electrode arrays with epidural placement allow establishing neural interfaces which promote investigation of complex distributed brain functions and development of neuroprosthetic systems while having reduced invasiveness in comparison to intracortical or subdural electrode placement. In this work, we present the design and fabrication of a flexible ECoG array with 202...
In this preliminary study, we explore the brain activity of healthy subjects during visual sustained attention task using a low-cost electroencephalography headset. The main objective is to study the ability of subjects to detect and respond to stimulus changes which occur infrequently during the time using Emotiv EPOC system. 14-Channels EEG data were recorded while subjects participated in 10 minutes...
Patients with disorders of consciousness (DOC) cannot reply to questions or clinical assessments using voluntary motor control, and therefore it is very difficult to assess their cognitive capabilities and conscious awareness. Patients who are locked-in (LIS) are instead fully conscious, and they can communicate with their preserved eye movements. However, when the residual oculomotor activity is...
In a recent past, several techniques have been developed to analyze the events contained in the electrohysterogram signals (EHG). But, the most of them focused on offline methods. In this study, we use an online method which is developed previously and known by Dynamic Cumulative Sum (DCS). The approach is applied on real EHG signals database through a 4×4 electrodes matrix. For this purpose, two...
In this paper we propose a biometric recognition system based on steady-state visual evoked potentials (SSVEPs), exploiting brain signals elicited by repetitive stimuli having a constant frequency as identifiers. EEG responses to SSVEP stimuli flickering at different frequencies are recorded, and both mel-frequency cepstral coefficients (MFCCs) and autoregressive (AR) reflection coefficients are used...
The information to be transmitted along the nervous system is encoded with the rate of fire of the neurons expressing the number of action potentials in a temporal range. Findings from experimental studies in the development of visual prosthetic systems, as a neuroprosthetic device, are of critical importance. The determination of the various working intervals required for the development of electronic...
Motor imagery is classified as either kinesthetic motor imagery (KMI) or visual motor imagery (VMI). However, investigations to evaluate the type and characteristics of motor imagery using electroencephalography (EEG) have been limited. Here we examined differences in EEG characteristics during KMI, VMI, and no motor imagery (NMI). Differences in EEG during movement execution (ME) and movement observation...
This study provides an insight into a novel steady state visually evoked potential (SSVEP) brain computer interface (BCI) approach. In this approach, four groups of light emitting diodes (LEDs) that flicker at different frequencies are used and each of these groups consist of three LEDs connected in series. By providing visual attention to these LEDs, corresponding electroencephalograph (EEG) signals...
Along with its clinical applications, EEG signals can be used in the biometric authentication domain based on its inimitable characteristics and uniqueness. Analyzed EEG signals are applied in many research studies as a communication trail between the human brain and the computer using BCI technology. In this paper, brain responses were triggered with visual stimulation of ten normal subjects. Biometric...
A visual Brain-Computer Interface (BCI) speller is a system which assists disabled persons with severe neu-romuscular diseases to communicate with the external world. It acquires brain signals in response to visual stimuli shown to the person on a screen, and then analyzes in real-time to predict the desired symbol on a single trial basis. To date most BCI design paradigms have been focused on the...
The purpose of the study is to observe the effect of the level of luminance on the emotional evaluation (positive, negative, neutral) in electroencephalography (EEG) records. EEG records of 31 healthy volunteers were used in the study. Features were obtained from these records by using Principle Component Analysis (PCA) method. As a result of the analysis of the features, it was observed that the...
Transcranial direct stimulation (tDCS) is a technique for modulating brain excitability that has potential to be used in motor neurorehabilitation by enhancing motor activity, such as motor imagery (MI). tDCS effects depend on different factors, like current density and the position of the stimulating electrodes. This study presents preliminary results of the evaluation of the effect of current density...
Error-Related Potentials (ErrPs) have been used lately in order to improve several existing Brain-Computer Interface (BCI) applications. In our study we investigate the contribution of ErrPs in a Steady State Visual Evoked Potential (SSVEP) based BCI. An extensive study is presented in order to discover the limitations of the proposed scheme. Using Common Spatial Patterns and Random Forests we manage...
A plethora of studies has shown that working memory, processing speed and fluid intelligence are diminished with aging. However, emotional processing remains relatively stable even though emotional processing alters through aging. Neurophysiological studies have employed emotional stimuli to investigate age differences through Event Related Potentials (ERPs). The present approach used affective visual...
Brain-computer interface (BCI) is a modern useful tool of bypassing usual channels of muscle and peripheral nervous system to establish a direct connection between brain and external devices and to restore fundamental communication and control skills. Steady-state visual evoked potential (SSVEP), as one of the most popular EEG modality, has been widely used in BCI applications. For SSVEP BCI, the...
In this work the design of a new epiretinal stimulator approach with integrated bendable imaging sensor is presented. First, the fundamental differences to the existing retinal stimulation implants is described. In the second part, a brief description of the novel designed implant is given, where several integrated circuits are placed on a single polyimide foil to create the mechanically flexible...
Visual function testing using electroretinogram (ERG) signal is used to detect abnormalities of the retina. This is accomplished by measuring, characterizing and analyzing the bio potential responses from various retinal cells formed due to a visual stimulation. The objective of this study is to improve the existing ERG signal characterization models by identifying and including a key component called...
Target image detection based on rapid serial visual presentation (RSVP) paradigm is a typical brain-computer interface with various applications, such as image retrieval. In an RSVP paradigm, the P300 component is detected to determine the target image, which requires high-precision single-trial P300 detection methods. However, compared to multi-trial P300 detection methods, the performance of single-trial...
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