Athanasios Vourvopoulos

Evaluation of commercial brain-computer interfaces in real and virtual world environment

Identify the users adaptation on brain-controlled systems.Ability to control brain-generated events.Control a robot in both real and virtual worlds via brainwaves. This paper identifies the users adaptation on brain-controlled systems and the ability to control brain-generated events in a closed neuro-feedback loop. The user experience is quantified for the further understanding of brain-computer interfacing. A working system has been developed based on off-the-shelf components for controlling a robot in both the real and virtual world. Using commercial brain-computer interfaces (BCIs) the overall cost, set up time and complexity can be reduced. The system is divided in two prototypes based on the headset type used. The first prototype is based on the Neurosky headset and it has been tested with 54 participants in a field study. The second prototype is based on the Emotiv headset including more sensors and accuracy, tested with 31 participants in a lab environment. Evaluation results indicate that robot navigation through commercial BCIs can be effective and natural both in the real and the virtual environment.

Brain-controlled serious games for cultural heritage

This paper proposes a prototype system for cultural heritage based on brain computer interfaces for navigating and interacting with serious games. By analyzing traditional human-computer interaction methods and paradigms with brain-controlled games it is possible to investigate novel methods for interacting and perceiving virtual heritage worlds. An interactive serious cultural heritage game was developed based on commercial BCI headsets controlling virtual aggents in the ancient city of Rome. Initial results indicate that brain computer technologies can be very useful for the creation of interactive serious games.

Robot Navigation Using Brain-Computer Interfaces

This paper identifies the users adaptation on brain-controlled systems and the ability to control brain-generated events in a closed neuro-feedback loop. To accomplish that, a working system has been developed based on off-the-shelf components for controlling a robot in both the real and virtual world. Using commercial Brain-Computer Interfaces (BCIs) the overall cost, set up time and complexity can be reduced. The system is divided in two prototypes based on the headset type used. The first prototype is based on the Neurosky headset and it has been tested with 54 participants. The second prototype is based on the Emotiv headset including more sensors and accuracy. Initial evaluation results indicate that robot navigation through commercial BCIs can be effective and natural.

Atmos: a hybrid crowdsourcing approach to weather estimation

Motivated by the novel paradigm of participatory sensing in collecting in situ automated data and human input we introduce the Atmos platform. Atmos leverages a crowd-sourcing network of mobile devices for the collection of in situ weather related sensory data, provided by available on-board sensors, along with human input, to generate highly localized information about current and future weather conditions. In this paper, we share our first insights of an 8-month long deployment of Atmos mobile app on Google Play that gathered data from a total of 9 countries across 3 continents. Furthermore, we describe the underlying system infrastructure and showcase how a hybrid people-centric and environment-centric approach to weather estimation could benefit forecasting. Finally, we present our preliminary results originating from questionnaires inquiring into how people perceive the weather, how they use technology to know about the weather and how it affects their habits.

Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis

BackgroundThe use of Brain–Computer Interface (BCI) technology in neurorehabilitation provides new strategies to overcome stroke-related motor limitations. Recent studies demonstrated the brains capacity for functional and structural plasticity through BCI. However, it is not fully clear how we can take full advantage of the neurobiological mechanisms underlying recovery and how to maximize restoration through BCI. In this study we investigate the role of multimodal virtual reality (VR) simulations and motor priming (MP) in an upper limb motor-imagery BCI task in order to maximize the engagement of sensory-motor networks in a broad range of patients who can benefit from virtual rehabilitation training.MethodsIn order to investigate how different BCI paradigms impact brain activation, we designed 3 experimental conditions in a within-subject design, including an immersive Multimodal Virtual Reality with Motor Priming (VRMP) condition where users had to perform motor-execution before BCI training, an immersive Multimodal VR condition, and a control condition with standard 2D feedback. Further, these were also compared to overt motor-execution. Finally, a set of questionnaires were used to gather subjective data on Workload, Kinesthetic Imagery and Presence.ResultsOur findings show increased capacity to modulate and enhance brain activity patterns in all extracted EEG rhythms matching more closely those present during motor-execution and also a strong relationship between electrophysiological data and subjective experience.ConclusionsOur data suggest that both VR and particularly MP can enhance the activation of brain patterns present during overt motor-execution. Further, we show changes in the interhemispheric EEG balance, which might play an important role in the promotion of neural activation and neuroplastic changes in stroke patients in a motor-imagery neurofeedback paradigm. In addition, electrophysiological correlates of psychophysiological responses provide us with valuable information about the motor and affective state of the user that has the potential to be used to predict MI-BCI training outcome based on user’s profile. Finally, we propose a BCI paradigm in VR, which gives the possibility of motor priming for patients with low level of motor control.

RehabCity: design and validation of a cognitive assessment and rehabilitation tool through gamified simulations of activities of daily living

Worldwide, more than one in three adults suffers from a cardiovascular disease. According to the World Health Organization, 15 million people experience a stroke each year and, of these, 5 million stay permanently disabled. The current limitations of traditional rehabilitation methods push towards the design of personalized tools that can be used intensively by patients and therapists in clinical or at-home environments. In this paper we present the design, implementation and validation of RehabCity, an online game designed for the rehabilitation of cognitive deficits through a gamified approach on activities of daily living (ADLs). Among other findings, our results show a strong correlation between the RehabCity scoring system and the Mini Mental State Examination test for clinical assessment of cognitive function in several domains. These findings suggest that RehabCity is a valid tool for the quantitative assessment of patients with cognitive deficits derived from a brain lesion.

Comparing interaction techniques for serious games through brain-computer interfaces:a user perception evaluation study

This paper examines the application of commercial and non-invasive electroencephalography (EEG)-based brain-computer (BCIs) interfaces with serious games. Two different EEG-based BCI devices were used to fully control the same serious game. The first device (NeuroSky MindSet) uses only a single dry electrode and requires no calibration. The second device (Emotiv EPOC) uses 14 wet sensors requiring additional training of a classifier. User testing was performed on both devices with sixty-two participants measuring the player experience as well as key aspects of serious games, primarily learnability, satisfaction, performance and effort. Recorded feedback indicates that the current state of BCIs can be used in the future as alternative game interfaces after familiarisation and in some cases calibration. Comparative analysis showed significant differences between the two devices. The first device provides more satisfaction to the players whereas the second device is more effective in terms of adaptation and interaction with the serious game.

EEG correlates of video game experience and user profile in motor-imagery-based brain---computer interaction

Through the use of brain–computer interfaces (BCIs), neurogames have become increasingly more advanced by incorporating immersive virtual environments and 3D worlds. However, training both the user and the system requires long and repetitive trials resulting in fatigue and low performance. Moreover, many users are unable to voluntarily modulate the amplitude of their brain activity to control the neurofeedback loop. In this study, we are focusing on the effect that gaming experience has in brain activity modulation as an attempt to systematically identify the elements that contribute to high BCI control and to be utilized in neurogame design. Based on the current literature, we argue that experienced gamers could have better performance in BCI training due to enhanced sensorimotor learning derived from gaming. To investigate this, two experimental studies were conducted with 20 participants overall, undergoing 3 BCI sessions, resulting in 88 EEG datasets. Results indicate (a) an effect from both demographic and gaming experience data to the activity patterns of EEG rhythms, and (b) increased gaming experience might not increase significantly performance, but it could provide faster learning for ‘Hardcore’ gamers.

Optimizing motor imagery neurofeedback through the use of multimodal immersive virtual reality and motor priming

Stroke is among the leading causes of long-term disability, leaving an increasing number of people with cognitive and motor impairments, loss of independence in their daily life and with a high societal cost. So far, the development of Brain-Computer Interfaces (BCIs) that translate brain activity into control signals in computers or external devices provide new strategies to overcome stroke-related motor limitations. Recent studies demonstrated the brains capacity for functional and structural plasticity and recovery even in severe chronic stroke. However, it is not fully clear how we can exploit the neurobiological mechanisms underlying recovery. This is the case for restorative BCI research. There is currently no standardized and accepted treatment for the use of BCIs with patients suffering from acute or chronic motor impairments. In this study we investigated with 9 healthy participants the role of multimodal virtual reality (VR) simulations and motor priming (MP) in a motor imagery BCI training. Our findings show improved BCI performance for VR and MP conditions, as well as the capacity to modulate and enhance brain activity patterns. Our data suggest that both VR and MP can be useful to promote neural activation and neuroplastic changes in the rehabilitation of stroke patients in a motor imagery neurofeedback paradigm.

Usability and Cost-effectiveness in Brain-Computer Interaction: Is it User Throughput or Technology Related?

In recent years, Brain-Computer Interfaces (BCIs) have been steadily gaining ground in the market, used either as an implicit or explicit input method in computers for accessibility, entertainment or rehabilitation. Past research in BCI has heavily neglected the human aspect in the loop, focusing mostly in the machine layer. Further, due to the high cost of current BCI systems, many studies rely on low-cost and low-quality equipment with difficulties to provide significant advancements in physiological computing. Open-Source projects are offered as alternatives to expensive medical equipment. Nevertheless, the effectiveness of such systems over their cost is still unclear, and whether they can deliver the same level of experience as their more expensive counterparts. In this paper, we demonstrate that effective BCI interaction in a Motor-Imagery BCI paradigm can be accomplished without requiring high-end/high-cost devices, by analyzing and comparing EEG systems ranging from open source devices to medically certified systems.