Using neurophysiological signals that reflect cognitive or affective state

What can we learn from spontaneously occurring brain and other physiological signals about an individual’s cognitive and affective state and how can we make use of this information? \ud \ud One line of research that is actively involved with this question is Passive Brain-Computer-Interfaces (BCI). To date most BCIs are aimed at assisting patients for whom brain signals could form an alternative output channel as opposed to more common human output channels, like speech and moving the hands. However, brain signals (possibly in combination with other physiological signals) also form an output channel above and beyond the more usual ones: they can potentially provide continuous, online information about an individual’s cognitive and affective state without the need of conscious or effortful communication. The provided information could be used in a number of ways. Examples include monitoring cognitive workload through EEG and skin conductance for adaptive automation or using ERPs in response to errors to correct for a behavioral response. While Passive BCIs make use of online (neuro)physiological responses and close the interaction cycle between a user and a computer system, (neuro)physiological responses can also be used in an offline fashion. Examples of this include detecting amygdala responses for neuromarketing, and measuring EEG and pupil dilation as indicators of mental effort for optimizing information systems. \ud \ud The described field of applied (neuro)physiology can strongly benefit from high quality scientific studies that control for confounding factors and use proper comparison conditions. Another area of relevance is ethics, ranging from dubious product claims, acceptance of the technology by the general public, privacy of users, to possible effects that these kinds of applications may have on society as a whole. \ud \ud In this Research Topic we aimed to publish studies of the highest scientific quality that are directed towards applications that utilize spontaneously, effortlessly generated neurophysiological signals (brain and/or other physiological signals) reflecting cognitive or affective state. We especially welcomed studies that describe specific real world applications demonstrating a significant benefit compared to standard applications. We also invited original, new kinds of (proposed) applications in this area as well as comprehensive review articles that point out what is and what is not possible (according to scientific standards) in this field. Finally, we welcomed manuscripts on the ethical issues that are involved. \ud \ud Connected to the Research Topic was a workshop (held on June 6, during the Fifth International Brain-Computer Interface Meeting, June 3-7, 2013, Asilomar, California) that brought together a diverse group of people who were working in this field. We discussed the state of the art and formulated major challenges, as reflected in the first paper of the Research Topic

Real-time vigilance estimation using mobile wireless mindo EEG device with spring-loaded sensors

Monitoring the neurophysiological activities of human brain dynamics in an operational environment poses a severe measurement challenge using current laboratory-oriented biosensor technology. The goal of this research is to design, develop and test the wearable and wireless dry-electrode EEG human-computer interface (HCI) that can allow assessment of brain activities of participants actively performing ordinary tasks in natural body positions and situations within a real operational environment. Its implications in HCI were demonstrated through a sample application: vigilance-state prediction of participants performing a realistic sustained-attention driving task. Besides, this study further developed an online signal processing for extracting EEG features and assessing cognitive performance. We demonstrated the feasibility of using dry EEG sensors and miniaturized supporting hardware/software to continuously collect EEG data recorded from hairy sites (i.e., occipital region) in a realistic VR-based dynamic driving simulator. © 2013 Springer-Verlag Berlin Heidelberg