A comparative study of stereo-dependent SSVEP targets and their impact on VR-BCI performance

Steady-state visual evoked potential brain-computer interfaces (SSVEP-BCI) have attracted significant attention due to their ease of deployment and high performance in terms of information transfer rate (ITR) and accuracy, making them a promising candidate for integration with consumer electronics devices. However, as SSVEP characteristics are directly associated with visual stimulus attributes, the influence of stereoscopic vision on SSVEP as a critical visual attribute has yet to be fully explored. Meanwhile, the promising combination of virtual reality (VR) devices and BCI applications is hampered by the significant disparity between VR environments and traditional 2D displays. This is not only due to the fact that screen-based SSVEP generally operates under static, stable conditions with simple and unvaried visual stimuli but also because conventional luminance-modulated stimuli can quickly induce visual fatigue. This study attempts to address these research gaps by designing SSVEP paradigms with stereo-related attributes and conducting a comparative analysis with the traditional 2D planar paradigm under the same VR environment. This study proposed two new paradigms: the 3D paradigm and the 3D-Blink paradigm. The 3D paradigm induces SSVEP by modulating the luminance of spherical targets, while the 3D-Blink paradigm employs modulation of the spheres' opacity instead. The results of offline 4-object selection experiments showed that the accuracy of 3D and 2D paradigm was 85.67 and 86.17% with canonical correlation analysis (CCA) and 86.17 and 91.73% with filter bank canonical correlation analysis (FBCCA), which is consistent with the reduction in the signal-to-noise ratio (SNR) of SSVEP harmonics for the 3D paradigm observed in the frequency-domain analysis. The 3D-Blink paradigm achieved 75.00% of detection accuracy and 27.02 bits/min of ITR with 0.8 seconds of stimulus time and task-related component analysis (TRCA) algorithm, demonstrating its effectiveness. These findings demonstrate that the 3D and 3D-Blink paradigms supported by VR can achieve improved user comfort and satisfactory performance, while further algorithmic optimization and feature analysis are required for the stereo-related paradigms. In conclusion, this study contributes to a deeper understanding of the impact of binocular stereoscopic vision mechanisms on SSVEP paradigms and promotes the application of SSVEP-BCI in diverse VR environments

Eliciting steady-state visual evoked potentials by means of stereoscopic displays

Brain-Computer Interfaces (BCIs) provide users communication and control capabilities by analyzing their brain activity. A technique to implement BCIs, used recently also in Virtual Reality (VR) environments, is based on the Steady State Visual Evoked Potentials (SSVEPs) detection. Exploiting the SSVEP response, BCIs could be implemented showing targets flickering at different frequencies and detecting which is gazed by the observer analyzing her/his electroencephalographic (EEG) signals. In this work, we evaluate the use of stereoscopic displays for the presentation of SSVEP eliciting stimuli, comparing their effectiveness between monoscopic and stereoscopic stimuli. Moreover we propose a novel method to elicit SSVEP responses exploiting the stereoscopic displays capability of presenting dichoptic stimuli. We have created an experimental scene to present flickering stimuli on an active stereoscopic display, obtaining reliable control of the targets' frequency independently for the two stereo views. Using an EEG acquisition device, we analyzed the SSVEP responses from a group of subjects. From the preliminary results, we got evidence that stereoscopic displays represent valid devices for the presentation of SSVEP stimuli. Moreover, the use of different flickering frequencies for the two views of a single stimulus proved to elicit non-linear interactions between the stimulation frequencies, clearly visible in the EEG signal. This suggests interesting applications for SSVEP-based BCIs in VR environments able to overcome some limitations imposed by the refresh frequency of standard displays, but also the use of commodity stereoscopic displays to implement binocular rivalry experiments

TOWARDS STEADY-STATE VISUALLY EVOKED POTENTIALS BRAIN-COMPUTER INTERFACES FOR VIRTUAL REALITY ENVIRONMENTS EXPLICIT AND IMPLICIT INTERACTION

In the last two decades, Brain-Computer Interfaces (BCIs) have been investigated mainly for the purpose of implementing assistive technologies able to provide new channels for communication and control for people with severe disabilities. Nevertheless, more recently, thanks to technical and scientific advances in the different research fields involved, BCIs are gaining greater attention also for their adoption by healthy users, as new interaction devices. This thesis is dedicated to to the latter goal and in particular will deal with BCIs based on the Steady State Visual Evoked Potential (SSVEP), which in previous works demonstrated to be one of the most flexible and reliable approaches. SSVEP based BCIs could find applications in different contexts, but one which is particularly interesting for healthy users, is their adoption as new interaction devices for Virtual Reality (VR) environments and Computer Games. Although being investigated since several years, BCIs still poses several limitations in terms of speed, reliability and usability with respect to ordinary interaction devices. Despite of this, they may provide additional, more direct and intuitive, explicit interaction modalities, as well as implicit interaction modalities otherwise impossible with ordinary devices. This thesis, after a comprehensive review of the different research fields being the basis of a BCI exploiting the SSVEP modality, present a state-of-the-art open source implementation using a mix of pre-existing and custom software tools. The proposed implementation, mainly aimed to the interaction with VR environments and Computer Games, has then been used to perform several experiments which are hereby described as well. Initially performed experiments aim to stress the validity of the provided implementation, as well as to show its usability with a commodity bio-signal acquisition device, orders of magnitude less expensive than commonly used ones, representing a step forward in the direction of practical BCIs for end users applications. The proposed implementation, thanks to its flexibility, is used also to perform novel experiments aimed to investigate the exploitation of stereoscopic displays to overcome a known limitation of ordinary displays in the context of SSVEP based BCIs. Eventually, novel experiments are presented investigating the use of the SSVEP modality to provide also implicit interaction. In this context, a first proof of concept Passive BCI based on the SSVEP response is presented and demonstrated to provide information exploitable for prospective applications

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Book of Abstracts 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and 3rd Conference on Imaging and Visualization

In this edition, the two events will run together as a single conference, highlighting the strong connection with the Taylor & Francis journals: Computer Methods in Biomechanics and Biomedical Engineering (John Middleton and Christopher Jacobs, Eds.) and Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (JoãoManuel R.S. Tavares, Ed.). The conference has become a major international meeting on computational biomechanics, imaging andvisualization. In this edition, the main program includes 212 presentations. In addition, sixteen renowned researchers will give plenary keynotes, addressing current challenges in computational biomechanics and biomedical imaging. In Lisbon, for the first time, a session dedicated to award the winner of the Best Paper in CMBBE Journal will take place. We believe that CMBBE2018 will have a strong impact on the development of computational biomechanics and biomedical imaging and visualization, identifying emerging areas of research and promoting the collaboration and networking between participants. This impact is evidenced through the well-known research groups, commercial companies and scientific organizations, who continue to support and sponsor the CMBBE meeting series. In fact, the conference is enriched with five workshops on specific scientific topics and commercial software.info:eu-repo/semantics/draf

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration

Exploiting physiological changes during the flow experience for assessing virtual-reality game design.

Immersive experiences are considered the principal attraction of video games. Achieving a healthy balance between the game's demands and the user's skills is a particularly challenging goal. However, it is a coveted outcome, as it gives rise to the flow experience – a mental state of deep concentration and game engagement. When this balance fractures, the player may experience considerable disinclination to continue playing, which may be a product of anxiety or boredom. Thus, being able to predict manifestations of these psychological states in video game players is essential for understanding player motivation and designing better games. To this end, we build on earlier work to evaluate flow dynamics from a physiological perspective using a custom video game. Although advancements in this area are growing, there has been little consideration given to the interpersonal characteristics that may influence the expression of the flow experience. In this thesis, two angles are introduced that remain poorly understood. First, the investigation is contextualized in the virtual reality domain, a technology that putatively amplifies affective experiences, yet is still insufficiently addressed in the flow literature. Second, a novel analysis setup is proposed, whereby the recorded physiological responses and psychometric self-ratings are combined to assess the effectiveness of our game's design in a series of experiments. The analysis workflow employed heart rate and eye blink variability, and electroencephalography (EEG) as objective assessment measures of the game's impact, and self-reports as subjective assessment measures. These inputs were submitted to a clustering method, cross-referencing the membership of the observations with self-report ratings of the players they originated from. Next, this information was used to effectively inform specialized decoders of the flow state from the physiological responses. This approach successfully enabled classifiers to operate at high accuracy rates in all our studies. Furthermore, we addressed the compression of medium-resolution EEG sensors to a minimal set required to decode flow. Overall, our findings suggest that the approaches employed in this thesis have wide applicability and potential for improving game designing practices