A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey

The growing interest in the Metaverse has generated momentum for members of academia and industry to innovate toward realizing the Metaverse world. The Metaverse is a unique, continuous, and shared virtual world where humans embody a digital form within an online platform. Through a digital avatar, Metaverse users should have a perceptual presence within the environment and can interact and control the virtual world around them. Thus, a human-centric design is a crucial element of the Metaverse. The human users are not only the central entity but also the source of multi-sensory data that can be used to enrich the Metaverse ecosystem. In this survey, we study the potential applications of Brain-Computer Interface (BCI) technologies that can enhance the experience of Metaverse users. By directly communicating with the human brain, the most complex organ in the human body, BCI technologies hold the potential for the most intuitive human-machine system operating at the speed of thought. BCI technologies can enable various innovative applications for the Metaverse through this neural pathway, such as user cognitive state monitoring, digital avatar control, virtual interactions, and imagined speech communications. This survey first outlines the fundamental background of the Metaverse and BCI technologies. We then discuss the current challenges of the Metaverse that can potentially be addressed by BCI, such as motion sickness when users experience virtual environments or the negative emotional states of users in immersive virtual applications. After that, we propose and discuss a new research direction called Human Digital Twin, in which digital twins can create an intelligent and interactable avatar from the user's brain signals. We also present the challenges and potential solutions in synchronizing and communicating between virtual and physical entities in the Metaverse

ON THE INTERPLAY BETWEEN BRAIN-COMPUTER INTERFACES AND MACHINE LEARNING ALGORITHMS: A SYSTEMS PERSPECTIVE

Today, computer algorithms use traditional human-computer interfaces (e.g., keyboard, mouse, gestures, etc.), to interact with and extend human capabilities across all knowledge domains, allowing them to make complex decisions underpinned by massive datasets and machine learning. Machine learning has seen remarkable success in the past decade in obtaining deep insights and recognizing unknown patterns in complex data sets, in part by emulating how the brain performs certain computations. As we increase our understanding of the human brain, brain-computer interfaces can benefit from the power of machine learning, both as an underlying model of how the brain performs computations and as a tool for processing high-dimensional brain recordings. The technology (machine learning) has come full circle and is being applied back to understanding the brain and any electric residues of the brain activity over the scalp (EEG). Similarly, domains such as natural language processing, machine translation, and scene understanding remain beyond the scope of true machine learning algorithms and require human participation to be solved. In this work, we investigate the interplay between brain-computer interfaces and machine learning through the lens of end-user usability. Specifically, we propose the systems and algorithms to enable synergistic and user-friendly integration between computers (machine learning) and the human brain (brain-computer interfaces). In this context, we provide our research contributions in two interrelated aspects by, (i) applying machine learning to solve challenges with EEG-based BCIs, and (ii) enabling human-assisted machine learning with EEG-based human input and implicit feedback.Ph.D

Recent Applications in Graph Theory

Graph theory, being a rigorously investigated field of combinatorial mathematics, is adopted by a wide variety of disciplines addressing a plethora of real-world applications. Advances in graph algorithms and software implementations have made graph theory accessible to a larger community of interest. Ever-increasing interest in machine learning and model deployments for network data demands a coherent selection of topics rewarding a fresh, up-to-date summary of the theory and fruitful applications to probe further. This volume is a small yet unique contribution to graph theory applications and modeling with graphs. The subjects discussed include information hiding using graphs, dynamic graph-based systems to model and control cyber-physical systems, graph reconstruction, average distance neighborhood graphs, and pure and mixed-integer linear programming formulations to cluster networks

Brain-Computer Interface

Brain-computer interfacing (BCI) with the use of advanced artificial intelligence identification is a rapidly growing new technology that allows a silently commanding brain to manipulate devices ranging from smartphones to advanced articulated robotic arms when physical control is not possible. BCI can be viewed as a collaboration between the brain and a device via the direct passage of electrical signals from neurons to an external system. The book provides a comprehensive summary of conventional and novel methods for processing brain signals. The chapters cover a range of topics including noninvasive and invasive signal acquisition, signal processing methods, deep learning approaches, and implementation of BCI in experimental problems

Novel technologies for the detection and mitigation of drowsy driving

In the human control of motor vehicles, there are situations regularly encountered wherein the vehicle operator becomes drowsy and fatigued due to the influence of long work days, long driving hours, or low amounts of sleep. Although various methods are currently proposed to detect drowsiness in the operator, they are either obtrusive, expensive, or otherwise impractical. The method of drowsy driving detection through the collection of Steering Wheel Movement (SWM) signals has become an important measure as it lends itself to accurate, effective, and cost-effective drowsiness detection. In this dissertation, novel technologies for drowsiness detection using Inertial Measurement Units (IMUs) are investigated and described. IMUs are an umbrella group of kinetic sensors (including accelerometers and gyroscopes) which transduce physical motions into data. Driving performances were recorded using IMUs as the primary sensors, and the resulting data were used by artificial intelligence algorithms, specifically Support Vector Machines (SVMs) to determine whether or not the individual was still fit to operate a motor vehicle. Results demonstrated high accuracy of the method in classifying drowsiness. It was also shown that the use of a smartphone-based approach to IMU monitoring of drowsiness will result in the initiation of feedback mechanisms upon a positive detection of drowsiness. These feedback mechanisms are intended to notify the driver of their drowsy state, and to dissuade further driving which could lead to crashes and/or fatalities. The novel methods not only demonstrated the ability to qualitatively determine a drivers drowsy state, but they were also low-cost, easy to implement, and unobtrusive to drivers. The efficacy, ease of use, and ease of access to these methods could potentially eliminate many barriers to the implementation of the technologies. Ultimately, it is hoped that these findings will help enhance traveler safety and prevent deaths and injuries to users

Apophenoesis & the Origins of Creativity: Virtual Pattern Recognition, Error, Paths to Consciousness & Augmenting the Evolution of Self

Erratum: the name Karl Conrad appears in the metadata abstract and on page 7 and page 19 of the file. This is an error and should read Klaus Conrad. LW (LDS) 20/10/20This research defines apophenoesis as a convergent practical tool that can enhance one’s creative process by introducing deviations from the familiar in such a way to allow new creative pathways to form and result in new innovations. With foundations in Roy Ascott’s technoetics, which is defined as a “convergent field of practice that seeks to explore consciousness and connectivity through digital, telematic, chemical or spiritual means, embracing both interactive and psychoactive technologies, and the creative use of moistmedia” (Ascott, 2008, p. 1), apophenoesis more specifically provides a framework to demonstrate the value of disruption within technoetic art while demonstrating the relationships between creativity and perception. I have conducted an auto-ethnomethodological approach to analyze my own creative practice, which culminated in the following apophenoetic artworks: Gesture's of Change (2013), Dabarithms (2014) and Poseidon's Pull: Revisited (2018). Each artwork represents the wide range of impact apophenoesis has had once integrated into the formation of artistic intent, establishment of the creative process, as well as the content experienced within the work of art by participants and observers. Since apophenoesis has a direct relationship to perception, it can be used both as a tool within the creative process as well as a mechanism within the content of the experience, thereby generating experiences of apophenoesis for participants within each technoetic artwork. In addition to Henri Bergson, who thoroughly models the relationship of perception to one’s reality, and Leonardo DaVinci, who used apophenoesis within his creative practice, a pivotal contributor to this research is the German psychiatrist, Karl Conrad, who discovered the phenomenon and called it apophanie during his clinical analysis of injured soldiers returning from war that exhibited what he then believed to be pre-schizophrenic characteristics. Conrad describes apophanie as phenomenon where one over-attributes significance in reference to patternless stimuli. This research highlights how Conrad’s discovery evolved into the establishment of the apophenoetic model and its relationship to interactive media art practice, culminating in the discovery that these characteristics can be used to define a new category of innovative practice entitled apophenoetic art. Rooted in technoetic arts, this practice-based research will reveal that the disruption introduced in applying apophenoesis to one’s creative practice is a fundamental tool to producing exponential boosts in creative productivity. Since Conrad’s clinical research found detailed evidence of how the mind mistakenly attributes significance via the senses through the perception of actual stimuli, his research regarding apophanie as being characteristic of an illness has been challenged. This introduces the consideration that the phenomenon may actually be a common, naturally occurring experience within the mind of healthy individuals, and often occurs subconsciously as a disruption in perception. How Conrad chose to define apophanie reveal his interest in fostering cross-disciplinary research. When apophenie is used in creative practice, it can be transformed into apophenoesis, or a method for accessing creativity and extending creative practice. Further analysis of apophenoesis reveals essential contributions to understanding the roots of creativity, inspiration, innovative thought, learning and how one’s mind and body work to access creativity

Effects of circadian rhythm phase alteration on physiological and psychological variables: Implications to pilot performance (including a partially annotated bibliography)

The effects of environmental synchronizers upon circadian rhythmic stability in man and the deleterious alterations in performance and which result from changes in this stability are points of interest in a review of selected literature published between 1972 and 1980. A total of 2,084 references relevant to pilot performance and circadian phase alteration are cited and arranged in the following categories: (1) human performance, with focus on the effects of sleep loss or disturbance and fatigue; (2) phase shift in which ground based light/dark alteration and transmeridian flight studies are discussed; (3) shiftwork; (4)internal desynchronization which includes the effect of evironmental factors on rhythmic stability, and of rhythm disturbances on sleep and psychopathology; (5) chronotherapy, the application of methods to ameliorate desynchronization symptomatology; and (6) biorythm theory, in which the birthdate based biorythm method for predicting aircraft accident susceptability is critically analyzed. Annotations are provided for most citations