Estimating Cognitive Workload in an Interactive Virtual Reality Environment Using EEG

With the recent surge of affordable, high-performance virtual reality (VR) headsets, there is unlimited potential for applications ranging from education, to training, to entertainment, to fitness and beyond. As these interfaces continue to evolve, passive user-state monitoring can play a key role in expanding the immersive VR experience, and tracking activity for user well-being. By recording physiological signals such as the electroencephalogram (EEG) during use of a VR device, the user\u27s interactions in the virtual environment could be adapted in real-time based on the user\u27s cognitive state. Current VR headsets provide a logical, convenient, and unobtrusive framework for mounting EEG sensors. The present study evaluates the feasibility of passively monitoring cognitive workload via EEG while performing a classical n-back task in an interactive VR environment. Data were collected from 15 participants and the spatio-spectral EEG features were analyzed with respect to task performance. The results indicate that scalp measurements of electrical activity can effectively discriminate three workload levels, even after suppression of a co-varying high-frequency activity

Using neurophysiological signals that reflect cognitive or affective state: Six recommendations to avoid common pitfalls

Estimating cognitive or affective state from neurophysiological signals and designing applications that make use of this information requires expertise in many disciplines such as neurophysiology, machine learning, experimental psychology, and human factors. This makes it difficult to perform research that is strong in all its aspects as well as to judge a study or application on its merits. On the occasion of the special topic “Using neurophysiological signals that reflect cognitive or affective state” we here summarize often occurring pitfalls and recommendations on how to avoid them, both for authors (researchers) and readers. They relate to defining the state of interest, the neurophysiological processes that are expected to be involved in the state of interest, confounding factors, inadvertently “cheating” with classification analyses, insight on what underlies successful state estimation, and finally, the added value of neurophysiological measures in the context of an application. We hope that this paper will support the community in producing high quality studies and well-validated, useful applications

The Berlin Brain–Computer Interface: Non-Medical Uses of BCI Technology

Brain–computer interfacing (BCI) is a steadily growing area of research. While initially BCI research was focused on applications for paralyzed patients, increasingly more alternative applications in healthy human subjects are proposed and investigated. In particular, monitoring of mental states and decoding of covert user states have seen a strong rise of interest. Here, we present some examples of such novel applications which provide evidence for the promising potential of BCI technology for non-medical uses. Furthermore, we discuss distinct methodological improvements required to bring non-medical applications of BCI technology to a diversity of layperson target groups, e.g., ease of use, minimal training, general usability, short control latencies

BRAIN COMPUTER INTERFACE (BCI) ON ATTENTION: A SCOPING REVIEW

Technological innovations are now an integral part of healthcare. Brain-computer interface (BCI) is a novel technological intervention system that is useful in restoring function to people disabled by neurological disorders such as attention deficit hyperactivity disorder (ADHD), amyotrophic lateral sclerosis (ALS), cerebral palsy, stroke, or spinal cord injury. This paper surveys the literature concerning the effectiveness of BCI on attention in subjects under various conditions. The findings of this scoping review are that studies have been made on ADHD, ALS, ASD subjects, and subjects recovering from brain and spinal cord injuries. BCI based neurofeedback training is seen to be effective in improving attention in these subjects. Some studies have also been made on healthy subjects.BCI based neurofeedback training promises neurocognitive improvement and EEG changes in the elderly. Different cognitive assessments have been tried on healthy adults.   From this review, it is evident that hardly any research has been done on using BCI for enhancing attention in post-stroke subjects. So there arises the necessity for making a study on the effects of BCI based attention training in post-stroke subjects, as attention is the key for learning motor skills that get impaired following a stroke. Currently, many researches are underway to determine the effects of a BCI based training program for the enhancement of attention in post-stroke subjects

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 299)

This bibliography lists 96 reports, articles, and other documents introduced into the NASA scientific and technical information system in June, 1987

Thought-controlled games with brain-computer interfaces

Nowadays, EEG based BCI systems are starting to gain ground in games for health research. With reduced costs and promising an innovative and exciting new interaction paradigm, attracted developers and researchers to use them on video games for serious applications. However, with researchers focusing mostly on the signal processing part, the interaction aspect of the BCIs has been neglected. A gap between classification performance and online control quality for BCI based systems has been created by this research disparity, resulting in suboptimal interactions that lead to user fatigue and loss of motivation over time. Motor-Imagery (MI) based BCIs interaction paradigms can provide an alternative way to overcome motor-related disabilities, and is being deployed in the health environment to promote the functional and structural plasticity of the brain. A BCI system in a neurorehabilitation environment, should not only have a high classification performance, but should also provoke a high level of engagement and sense of control to the user, for it to be advantageous. It should also maximize the level of control on user’s actions, while not requiring them to be subject to long training periods on each specific BCI system. This thesis has two main contributions, the Adaptive Performance Engine, a system we developed that can provide up to 20% improvement to user specific performance, and NeuRow, an immersive Virtual Reality environment for motor neurorehabilitation that consists of a closed neurofeedback interaction loop based on MI and multimodal feedback while using a state-of-the-art Head Mounted Display.Hoje em dia, os sistemas BCI baseados em EEG estão a começar a ganhar terreno em jogos relacionados com a saúde. Com custos reduzidos e prometendo um novo e inovador paradigma de interação, atraiu programadores e investigadores para usá-los em vídeo jogos para aplicações sérias. No entanto, com os investigadores focados principalmente na parte do processamento de sinal, o aspeto de interação dos BCI foi negligenciado. Um fosso entre o desempenho da classificação e a qualidade do controle on-line para sistemas baseados em BCI foi criado por esta disparidade de pesquisa, resultando em interações subótimas que levam à fadiga do usuário e à perda de motivação ao longo do tempo. Os paradigmas de interação BCI baseados em imagética motora (IM) podem fornecer uma maneira alternativa de superar incapacidades motoras, e estão sendo implementados no sector da saúde para promover plasticidade cerebral funcional e estrutural. Um sistema BCI usado num ambiente de neuro-reabilitação, para que seja vantajoso, não só deve ter um alto desempenho de classificação, mas também deve promover um elevado nível de envolvimento e sensação de controlo ao utilizador. Também deve maximizar o nível de controlo nas ações do utilizador, sem exigir que sejam submetidos a longos períodos de treino em cada sistema BCI específico. Esta tese tem duas contribuições principais, o Adaptive Performance Engine, um sistema que desenvolvemos e que pode fornecer até 20% de melhoria para o desempenho específico do usuário, e NeuRow, um ambiente imersivo de Realidade Virtual para neuro-reabilitação motora, que consiste num circuito fechado de interação de neuro-feedback baseado em IM e feedback multimodal e usando um Head Mounted Display de última geração

Electroencephalography (EEG), electromyography (EMG) and eye-tracking for astronaut training and space exploration

The ongoing push to send humans back to the Moon and to Mars is giving rise to a wide range of novel technical solutions in support of prospective astronaut expeditions. Against this backdrop, the European Space Agency (ESA) has recently launched an investigation into unobtrusive interface technologies as a potential answer to such challenges. Three particular technologies have shown promise in this regard: EEG-based brain-computer interfaces (BCI) provide a non-invasive method of utilizing recorded electrical activity of a user's brain, electromyography (EMG) enables monitoring of electrical signals generated by the user's muscle contractions, and finally, eye tracking enables, for instance, the tracking of user's gaze direction via camera recordings to convey commands. Beyond simply improving the usability of prospective technical solutions, our findings indicate that EMG, EEG, and eye-tracking could also serve to monitor and assess a variety of cognitive states, including attention, cognitive load, and mental fatigue of the user, while EMG could furthermore also be utilized to monitor the physical state of the astronaut. In this paper, we elaborate on the key strengths and challenges of these three enabling technologies, and in light of ESA's latest findings, we reflect on their applicability in the context of human space flight. Furthermore, a timeline of technological readiness is provided. In so doing, this paper feeds into the growing discourse on emerging technology and its role in paving the way for a human return to the Moon and expeditions beyond the Earth's orbit