Search

Effective use of brain-computer interfaces (BCIs) typically requires training. Improved understanding of the neural mechanisms underlying BCI training will facilitate optimisation of BCIs. The current study examined the neural mechanisms related to training for electroencephalography (EEG)-based communication with an auditory event-related potential (ERP) BCI. Neural mechanisms of training in 10 healthy volunteers were assessed with functional magnetic resonance imaging (fMRI) during an auditory ERP-based BCI task before (t1) and after (t5) three ERP-BCI training sessions outside the fMRI scanner (t2, t3, and t4). Attended stimuli were contrasted with ignored stimuli in the first-level fMRI data analysis (t1 and t5); the training effect was verified using the EEG data (t2-t4); and brain activation was contrasted before and after training in the second-level fMRI data analysis (t1 vs. t5). Training increased the communication speed from 2.9 bits/min (t2) to 4 bits/min (t4). Strong activation was found in the putamen, supplementary motor area (SMA), and superior temporal gyrus (STG) associated with attention to the stimuli. Training led to decreased activation in the superior frontal gyrus and stronger haemodynamic rebound in the STG and supramarginal gyrus. The neural mechanisms of ERP-BCI training indicate improved stimulus perception and reduced mental workload. The ERP task used in the current study showed overlapping activations with a motor imagery based BCI task from a previous study on the neural mechanisms of BCI training in the SMA and putamen. This suggests commonalities between the neural mechanisms of training for both BCI paradigms., (© 2019 Wiley Periodicals, Inc.)

Background: Eye trackers are widely used among people with amyotrophic lateral sclerosis, and their benefits to quality of life have been previously shown. On the contrary, Brain-computer interfaces (BCIs) are still quite a novel technology, which also serves as an access technology for people with severe motor impairment., Objective: To compare a visual P300-based BCI and an eye tracker in terms of information transfer rate (ITR), usability, and cognitive workload in users with motor impairments., Methods: Each participant performed 3 spelling tasks, over 4 total sessions, using an Internet browser, which was controlled by a spelling interface that was suitable for use with either the BCI or the eye tracker. At the end of each session, participants evaluated usability and cognitive workload of the system., Results: ITR and System Usability Scale (SUS) score were higher for the eye tracker (Wilcoxon signed-rank test: ITR T = 9, P = .016; SUS T = 12.50, P = .035). Cognitive workload was higher for the BCI (T = 4; P = .003)., Conclusions: Although BCIs could be potentially useful for people with severe physical disabilities, we showed that the usability of BCIs based on the visual P300 remains inferior to eye tracking. We suggest that future research on visual BCIs should use eye tracking-based control as a comparison to evaluate performance or focus on nonvisual paradigms for persons who have lost gaze control., (© The Author(s) 2015.)

Background: In this study, we evaluated electrooculography (EOG), an eye tracker and an auditory brain-computer interface (BCI) as access methods to augmentative and alternative communication (AAC). The participant of the study has been in the locked-in state (LIS) for 6 years due to amyotrophic lateral sclerosis. He was able to communicate with slow residual eye movements, but had no means of partner independent communication. We discuss the usability of all tested access methods and the prospects of using BCIs as an assistive technology., Methods: Within four days, we tested whether EOG, eye tracking and a BCI would allow the participant in LIS to make simple selections. We optimized the parameters in an iterative procedure for all systems., Results: The participant was able to gain control over all three systems. Nonetheless, due to the level of proficiency previously achieved with his low-tech AAC method, he did not consider using any of the tested systems as an additional communication channel. However, he would consider using the BCI once control over his eye muscles would no longer be possible. He rated the ease of use of the BCI as the highest among the tested systems, because no precise eye movements were required; but also as the most tiring, due to the high level of attention needed to operate the BCI., Conclusions: In this case study, the partner based communication was possible due to the good care provided and the proficiency achieved by the interlocutors. To ease the transition from a low-tech AAC method to a BCI once control over all muscles is lost, it must be simple to operate. For persons, who rely on AAC and are affected by a progressive neuromuscular disease, we argue that a complementary approach, combining BCIs and standard assistive technology, can prove valuable to achieve partner independent communication and ease the transition to a purely BCI based approach. Finally, we provide further evidence for the importance of a user-centered approach in the design of new assistive devices.

Objective: Brain-computer interfaces (BCI) based on event-related potentials (ERP) were proven to be a reliable synchronous communication method. For everyday life situations, however, this synchronous mode is impractical because the system will deliver a selection even if the user is not paying attention to the stimulation. So far, research into attention-aware visual ERP-BCIs (i.e., asynchronous ERP-BCIs) has led to variable success. In this study, we investigate new approaches for detection of user engagement., Approach: Classifier output and frequency-domain features of electroencephalogram signals as well as the hybridization of them were used to detect the user's state. We tested their capabilities for state detection in different control scenarios on offline data from 21 healthy volunteers., Main Results: The hybridization of classifier output and frequency-domain features outperformed the results of the single methods, and allowed building an asynchronous P300-based BCI with an average correct state detection accuracy of more than 95%., Significance: Our results show that all introduced approaches for state detection in an asynchronous P300-based BCI can effectively avoid involuntary selections, and that the hybrid method is the most effective approach.

Objectives: Access to the world wide web and multimedia content is an important aspect of life. We present a web browser and a multimedia user interface adapted for control with a brain-computer interface (BCI) which can be used by severely motor impaired persons., Methods: The web browser dynamically determines the most efficient P300 BCI matrix size to select the links on the current website. This enables control of the web browser with fewer commands and smaller matrices. The multimedia player was based on an existing software. Both applications were evaluated with a sample of ten healthy participants and three end-users. All participants used a visual P300 BCI with face-stimuli for control., Results: The healthy participants completed the multimedia player task with 90% accuracy and the web browsing task with 85% accuracy. The end-users completed the tasks with 62% and 58% accuracy. All healthy participants and two out of three end-users reported that they felt to be in control of the system., Conclusions: In this study we presented a multimedia application and an efficient web browser implemented for control with a BCI., Significance: Both applications provide access to important areas of modern information retrieval and entertainment., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users' home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user-centred design approach. The final BackHome system is the result of a 3-year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle-free BCI equipment; one-click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life.

The study aimed at revealing electrophysiological indicators of mental workload and fatigue during prolonged usage of a P300 brain-computer interface (BCI). Mental workload was experimentally manipulated with dichotic listening tasks. Medium and high workload conditions alternated. Behavioral measures confirmed that the manipulation of mental workload was successful. Reduced P300 amplitude was found for the high workload condition. Along with lower performance and an increase in the subjective level of fatigue, an increase of power in the alpha band was found for the last as compared to the first run of both conditions. The study confirms that a combination of signals derived from the time and frequency domain of the electroencephalogram is promising for the online detection of workload and fatigue. It also demonstrates that satisfactory accuracies can be achieved by healthy participants with the P300 speller, despite constant distraction and when pursuing the task for a long time., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Brain-computer interface (BCI) users can control very complex applications such as multimedia players or even web browsers. Therefore, different biosignal acquisition systems are available to noninvasively measure the electrical activity of the brain, the electroencephalogram (EEG). To make BCIs more practical, hardware and software are nowadays designed more user centered and user friendly. In this paper we evaluated one of the latest innovations in the area of BCI: A wireless EEG amplifier with dry electrode technology combined with a web browser which enables BCI users to use standard webmail. With this system ten volunteers performed a daily life task: Write, read and answer an email. Experimental results of this study demonstrate the power of the introduced BCI system.

Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a suitable BCI paradigm. Eleven severely motor impaired participants performed three sessions of a P300 BCI web browsing task. Before each session auditory oddball data were collected to predict the BCI aptitude of the participants exhibited in the current session. We found a strong relationship of early positive and negative potentials around 200 ms (elicited with the auditory oddball task) with performance. The amplitude of the P2 (r  =  -0.77) and of the N2 (r  =  -0.86) had the strongest correlations. Aptitude prediction using an auditory oddball was successful. The finding that the N2 amplitude is a stronger predictor of performance than P3 amplitude was reproduced after initially showing this effect with a healthy sample of BCI users. This will reduce strain on the end-users by minimizing the time needed to find suitable paradigms and inspire new approaches to improve performance.

Background: For many years the reestablishment of communication for people with severe motor paralysis has been in the focus of brain-computer interface (BCI) research. Recently applications for entertainment have also been developed. Brain Painting allows the user creative expression through painting pictures., Objective: The second, revised prototype of the BCI Brain Painting application was evaluated in its target function - free painting - and compared to the P300 spelling application by four end users with severe disabilities., Methods: According to the International Organization for Standardization (ISO), usability was evaluated in terms of effectiveness (accuracy), efficiency (information transfer rate (ITR)), utility metric, subjective workload (National Aeronautics and Space Administration Task Load Index (NASA TLX)) and user satisfaction (Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) 2.0 and Assistive Technology Device Predisposition Assessment (ATD PA), Device Form)., Results: The results revealed high performance levels (M≥80% accuracy) in the free painting and the copy painting conditions, ITRs (4.47-6.65bits/min) comparable to other P300 applications and only low to moderate workload levels (5-49 of 100), thereby proving that the complex task of free painting did neither impair performance nor impose insurmountable workload. Users were satisfied with the BCI Brain Painting application. Main obstacles for use in daily life were the system operability and the EEG cap, particularly the need of extensive support for adjustment., Conclusion: The P300 Brain Painting application can be operated with high effectiveness and efficiency. End users with severe motor paralysis would like to use the application in daily life. User-friendliness, specifically ease of use, is a mandatory necessity when bringing BCI to end users. Early and active involvement of users and iterative user-centered evaluation enable developers to work toward this goal., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Objectives: The main objective of the current study was to implement and evaluate a P300 based brain-computer interface (BCI) speller that uses directional cues of auditory stimuli, which are presented over headphones. The interstimulus interval (ISI) was successively reduced to determine the optimal combination of speed and accuracy. The study further aimed at quantifying the differences in subjective workload between the auditory and the visual P300 spelling application. The influence of workload, mood and motivation on BCI performance and P300 amplitude was investigated., Methods: Twenty healthy participants performed auditory and visual spelling tasks in an EEG experiment with online feedback., Results: Sixteen of twenty participants performed at or above a level necessary for satisfactory communication (≥70% spelling accuracy) with the auditory BCI. Average bit rates of up to 2.76 bits/min (best subject 7.43 bits/min) were achieved. A significantly higher workload was reported for the auditory speller compared to the visual paradigm. Motivation significantly influenced P300 amplitude at Pz in the auditory condition., Conclusions: The results of the online study suggest that the proposed paradigm offers a means of communication for most healthy users., Significance: The described auditory BCI can serve as a communication channel for completely paralyzed patients., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: To determine if brain-computer interfaces (BCIs) could serve as supportive tools for detecting consciousness in patients with disorders of consciousness by detecting response to command and communication., Methods: We tested a 4-choice auditory oddball EEG-BCI paradigm on 16 healthy subjects and 18 patients in a vegetative state/unresponsive wakefulness syndrome, in a minimally conscious state (MCS), and in locked-in syndrome (LIS). Subjects were exposed to 4 training trials and 10 -12 questions., Results: Thirteen healthy subjects and one LIS patient were able to communicate using the BCI. Four of those did not present with a P3. One MCS patient showed command following with the BCI while no behavioral response could be detected at bedside. All other patients did not show any response to command and could not communicate with the BCI., Conclusion: The present study provides evidence that EEG based BCI can detect command following in patients with altered states of consciousness and functional communication in patients with locked-in syndrome. However, BCI approaches have to be simplified to increase sensitivity., Significance: For some patients without any clinical sign of consciousness, a BCI might bear the potential to employ a "yes-no" spelling device offering the hope of functional interactive communication., (Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

Objective: Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball., Methods: Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude., Results: Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy., Conclusions: Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection., Significance: Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.

Brain computer interface (BCI) technology has been proposed for motor neurorehabilitation, motor replacement and assistive technologies. It is an open question whether proprioceptive feedback affects the regulation of brain oscillations and therefore BCI control. We developed a BCI coupled on-line with a robotic hand exoskeleton for flexing and extending the fingers. 24 healthy participants performed five different tasks of closing and opening the hand: (1) motor imagery of the hand movement without any overt movement and without feedback, (2) motor imagery with movement as online feedback (participants see and feel their hand, with the exoskeleton moving according to their brain signals, (3) passive (the orthosis passively opens and closes the hand without imagery) and (4) active (overt) movement of the hand and rest. Performance was defined as the difference in power of the sensorimotor rhythm during motor task and rest and calculated offline for different tasks. Participants were divided in three groups depending on the feedback receiving during task 2 (the other tasks were the same for all participants). Group 1 (n = 9) received contingent positive feedback (participants' sensorimotor rhythm (SMR) desynchronization was directly linked to hand orthosis movements), group 2 (n = 8) contingent "negative" feedback (participants' sensorimotor rhythm synchronization was directly linked to hand orthosis movements) and group 3 (n = 7) sham feedback (no link between brain oscillations and orthosis movements). We observed that proprioceptive feedback (feeling and seeing hand movements) improved BCI performance significantly. Furthermore, in the contingent positive group only a significant motor learning effect was observed enhancing SMR desynchronization during motor imagery without feedback in time. Furthermore, we observed a significantly stronger SMR desynchronization in the contingent positive group compared to the other groups during active and passive movements. To summarize, we demonstrated that the use of contingent positive proprioceptive feedback BCI enhanced SMR desynchronization during motor tasks.

The ideal brain–computer interface (BCI) adapts to the user's state to enable optimal BCI performance. Two methods of BCI adaptation are commonly applied: User-centered design (UCD) responds to individual user needs and requirements. Passive BCIs can adapt via online analysis of electrophysiological signals. Despite similar goals, these methods are rarely discussed in combination. Hence, we organized a workshop for the 8th International BCI Meeting 2021 to discuss the combined application of both methods. Here we expand upon the workshop by discussing UCD in more detail regarding its utility for end-users as well as non-end-user-based early-stage BCI development. Furthermore, we explore electrophysiology-based online user state adaptation concerning consciousness and pain detection. The integration of the numerous BCI user state adaptation methods into a unified process remains challenging. Yet, further systematic accumulation of specific knowledge about assessment and integration of internal user states bears great potential for BCI optimization. [ABSTRACT FROM AUTHOR]

The Eighth International Brain–Computer Interface (BCI) Meeting was held June 7–9, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering the breadth of topics in BCI (also called brain–machine interface) research. Some workshops provided detailed examinations of methods, hardware, or processes. Others focused on BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and improve comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, summarizes discussions, and describes the resulting conclusion, challenges, or initiatives. [ABSTRACT FROM AUTHOR]

Severe motor impairments can affect the ability to communicate. The ability to see has a decisive influence on the augmentative and alternative communication (AAC) systems available to the user. To better understand the initial impressions users have of AAC systems we asked naïve healthy participants to compare two visual (a visual P300 brain-computer interface (BCI) and an eye-tracker) and two non-visual systems (an auditory and a tactile P300 BCI). Eleven healthy participants performed 20 selections in a five choice task with each system. The visual P300 BCI used face stimuli, the auditory P300 BCI used Japanese Hiragana syllables and the tactile P300 BCI used a stimulator on the small left finger, middle left finger, right thumb, middle right finger and small right finger. The eye-tracker required a dwell time of 3 s on the target for selection. We calculated accuracies and information-transfer rates (ITRs) for each control method using the selection time that yielded the highest ITR and an accuracy above 70% for each system. Accuracies of 88% were achieved with the visual P300 BCI (4.8 s selection time, 20.9 bits/min), of 70% with the auditory BCI (19.9 s, 3.3 bits/min), of 71% with the tactile BCI (18 s, 3.4 bits/min) and of 100% with the eye-tracker (5.1 s, 28.2 bits/min). Performance between eye-tracker and visual BCI correlated strongly, correlation between tactile and auditory BCI performance was lower. Our data showed no advantage for either non-visual system in terms of ITR but a lower correlation of performance which suggests that choosing the system which suits a particular user is of higher importance for non-visual systems than visual systems. [ABSTRACT FROM AUTHOR]

Brain-Computer Interfaces (BCIs) provide communication channels independent from muscular control. In the current study we used two versions of the P300-BCI: one based on visual the other on auditory stimulation. Up to now, data on the impact of psychological variables on P300-BCI control are scarce. Hence, our goal was to identify new predictors with a comprehensive psychological test-battery. A total of N = 40 healthy BCI novices took part in a visual and an auditory BCI session. Psychological variables weremeasured with an electronic test-battery including clinical, personality, and performance tests. The personality factor "emotional stability" was negatively correlated (Spearman's rho = -0.416; p < 0.01) and an output variable of the non-verbal learning test (NVLT), which can be interpreted as ability to learn, correlated positively (Spearman's rho = 0.412; p < 0.01) with visual P300-BCI performance. In a linear regression analysis both independent variables explained 24% of the variance. "Emotional stability" was also negatively related to auditory P300-BCI performance (Spearman's rho = -0.377; p < 0.05), but failed significance in the regression analysis. Psychological parameters seem to play a moderate role in visual P300-BCI performance. "Emotional stability" was identified as a new predictor, indicating that BCI users who characterize themselves as calm and rational showed worse BCI performance. The positive relation of the ability to learn and BCI performance corroborates the notion that also for P300 based BCIs learning may constitute an important factor. Further studies are needed to consolidate or reject the presented predictors. [ABSTRACT FROM AUTHOR]

Current brain-computer interface (BCIs) software is often tailored to the needs of scientists and technicians and therefore complex to allow for versatile use. To facilitate home use of BCIs a multifunctional P300 BCI with a graphical user interface intended for non-expert set-up and control was designed and implemented. The system includes applications for spelling, web access, entertainment, artistic expression and environmental control. In addition to new software, it also includes new hardware for the recording of electroencephalogram (EEG) signals. The EEG system consists of a small and wireless amplifier attached to a cap that can be equipped with gel-based or dry contact electrodes. The system was systematically evaluated with a healthy sample, and targeted end users of BCI technology, i.e., people with a varying degree of motor impairment tested the BCI in a series of individual case studies. Usability was assessed in terms of effectiveness, efficiency and satisfaction. Feedback of users was gathered with structured questionnaires. Two groups of healthy participants completed an experimental protocol with the gel-based and the dry contact electrodes (N = 10 each). The results demonstrated that all healthy participants gained control over the system and achieved satisfactory to high accuracies with both gel-based and dry electrodes (average error rates of 6 and 13%). Average satisfaction ratings were high, but certain aspects of the system such as the wearing comfort of the dry electrodes and design of the cap, and speed (in both groups) were criticized by some participants. Six potential end users tested the system during supervised sessions. The achieved accuracies varied greatly from no control to high control with accuracies comparable to that of healthy volunteers. Satisfaction ratings of the two end-users that gained control of the system were lower as compared to healthy participants. The advantages and disadvantages of the BCI and its applications are discussed and suggestions are presented for improvements to pave the way for user friendly BCIs intended to be used as assistive technology by persons with severe paralysis. [ABSTRACT FROM AUTHOR]

Gaze-independent brain-computer interfaces (BCIs) are a possible communication channel for persons with paralysis. We investigated if it is possible to use auditory stimuli to create a BCI for the Japanese Hiragana syllabary, which has 46 Hiragana characters. Additionally, we investigated if training has an effect on accuracy despite the high amount of different stimuli involved. Able-bodied participants (N = 6) were asked to select 25 syllables (out of fifty possible choices) using a two step procedure: First the consonant (ten choices) and then the vowel (five choices). This was repeated on 3 separate days. Additionally, a person with spinal cord injury (SCI) participated in the experiment. Four out of six healthy participants reached Hiragana syllable accuracies above 70% and the information transfer rate increased from 1.7 bits/min in the first session to 3.2 bits/min in the third session. The accuracy of the participant with SCI increased from 12% (0.2 bits/min) to 56% (2 bits/min) in session three. Reliable selections from a 10 × 5 matrix using auditory stimuli were possible and performance is increased by training. We were able to show that auditory P300 BCIs can be used for communication with up to fifty symbols. This enables the use of the technology of auditory P300 BCIs with a variety of applications. [ABSTRACT FROM AUTHOR]

Brain-Computer Interfaces (BCIs) transfer human brain activities into computer commands and enable a communication channel without requiring movement. Among other BCI approaches, steady-state visual evoked potential (SSVEP)-based BCIs have the potential to become accurate, assistive technologies for persons with severe disabilities. Those systems require customization of different kinds of parameters (e.g., stimulation frequencies). Calibration usually requires selecting predefined parameters by experienced/trained personnel, though in real-life scenarios an interface allowing people with no experience in programming to set up the BCI would be desirable. Another occurring problem regarding BCI performance is BCI illiteracy (also called BCI deficiency). Many articles reported that BCI control could not be achieved by a non-negligible number of users. In order to bypass those problems we developed a SSVEP-BCI wizard, a system that automatically determines user-dependent key-parameters to customize SSVEP-based BCI systems. This wizard was tested and evaluated with 61 healthy subjects. All subjects were asked to spell the phrase "RHINE WAAL UNIVERSITY" with a spelling application after key parameters were determined by the wizard. Results show that all subjects were able to control the spelling application. A mean (SD) accuracy of 97.14 (3.73)% was reached (all subjects reached an accuracy above 85% and 25 subjects even reached 100% accuracy). [ABSTRACT FROM AUTHOR]

The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users’ home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user-centred design approach. The final BackHome system is the result of a 3-year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle-free BCI equipment; one-click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life. [ABSTRACT FROM AUTHOR]

Brain-computer interfaces (BCIs) can serve as muscle independent communication aids. Persons, who are unable to control their eye muscles (e.g., in the completely locked-in state) or have severe visual impairments for other reasons, need BCI systems that do not rely on the visual modality. For this reason, BCIs that employ auditory stimuli were suggested. In this study, a multiclass BCI spelling system was implemented that uses animal voices with directional cues to code rows and columns of a letter matrix. To reveal possible training effects with the system, 11 healthy participants performed spelling tasks on 2 consecutive days. In a second step, the system was tested by a participant with amyotrophic lateral sclerosis (ALS) in two sessions. In the first session, healthy participants spelled with an average accuracy of 76% (3.29 bits/min) that increased to 90% (4.23 bits/min) on the second day. Spelling accuracy by the participant with ALS was 20% in the first and 47% in the second session. The results indicate a strong training effect for both the healthy participants and the participant with ALS. While healthy participants reached high accuracies in the first session and second session, accuracies for the participant with ALS were not sufficient for satisfactory communication in both sessions. More training sessions might be needed to improve spelling accuracies. The study demonstrated the feasibility of the auditory BCI with healthy users and stresses the importance of training with auditory multiclass BCIs, especially for potential end-users of BCI with disease. [ABSTRACT FROM AUTHOR]

Patients in the completely locked-in state have no means of communication and they represent the target population for brain–computer interface research in the last 15 years. Although different paradigms have been tested and different physiological signals used, to date no sufficiently documented completely locked-in state patient was able to control a brain–computer interface over an extended time period. We introduce Pavlovian semantic conditioning to enable basic communication in completely locked-in state. This novel paradigm is based on semantic conditioning for online classification of neuroelectric or any other physiological signals to discriminate between covert (cognitive) ‘yes’ and ‘no’ responses. The paradigm comprised the presentation of affirmative and negative statements used as conditioned stimuli, while the unconditioned stimulus consisted of electrical stimulation of the skin paired with affirmative statements. Three patients with advanced amyotrophic lateral sclerosis participated over an extended time period, one of which was in a completely locked-in state, the other two in the locked-in state. The patients’ level of vigilance was assessed through auditory oddball procedures to study the correlation between vigilance level and the classifier’s performance. The average online classification accuracies of slow cortical components of electroencephalographic signals were around chance level for all the patients. The use of a non-linear classifier in the offline classification procedure resulted in a substantial improvement of the accuracy in one locked-in state patient achieving 70% correct classification. A reliable level of performance in the completely locked-in state patient was not achieved uniformly throughout the 37 sessions despite intact cognitive processing capacity, but in some sessions communication accuracies up to 70% were achieved. Paradigm modifications are proposed. Rapid drop of vigilance was detected suggesting attentional variations or variations of circadian period as important factors in brain–computer interface communication with locked-in state and completely locked-in state. [ABSTRACT FROM AUTHOR]

The aim of the study was to investigate conditioned electroencephalography (EEG) responses to factually correct and incorrect statements in order to enable binary communication by means of a brain-computer interface (BCI). In two experiments with healthy participants true and false statements (serving as conditioned stimuli, CSs) were paired with two different tones which served as unconditioned stimuli (USs). The features of the USs were varied and tested for their effectiveness to elicit differentiable conditioned reactions (CRs). After acquisition of the CRs, these CRs to true and false statements were classified offline using a radial basis function kernel support vector machine. A mean single-trial classification accuracy of 50.5% was achieved for differentiating conditioned "yes" versus "no" thinking and mean accuracies of 65.4% for classification of "yes" and 68.8% for "no" thinking (both relative to baseline) were found using the best US. Analysis of the area under the curve of the conditioned EEG responses revealed significant differences between conditioned "yes" and "no" answers. Even though improvements are necessary, these first results indicate that the semantic conditioning paradigm could be a useful basis for further research regarding BCI communication in patients in the complete locked-in state. [ABSTRACT FROM AUTHOR]

Abstract: Background: After about 30 years of research on Brain–Computer Interfaces (BCIs) there is little knowledge about the phenomenon, that some people - healthy as well as individuals with disease – are not able to learn BCI-control. To elucidate this “BCI-inefficiency” phenomenon, the current study investigated whether psychological parameters, such as attention span, personality or motivation, could predict performance in a single session with a BCI controlled by modulation of sensorimotor rhythms (SMR) with motor imagery. Methods: A total of N =83 healthy BCI novices took part in the session. Psychological parameters were measured with an electronic test-battery including clinical, personality and performance tests. Predictors were determined by binary logistic regression analyses. Results: The output variable of the Two-Hand Coordination Test (2HAND) “overall mean error duration” which is a measure for the accuracy of fine motor skills accounted for 11% of the variance in BCI-inefficiency. The Attitudes Towards Work (AHA) test variable “performance level” which can be interpreted as a degree of concentration and a neurophysiological SMR predictor were also identified as significant predictors of SMR BCI performance. Conclusion: Psychological parameters as measured in this study play a moderate role for one-session performance in a BCI controlled by modulation of SMR. [Copyright &y& Elsevier]

An electroencephalographic (EEG) brain–computer interface (BCI) internet browser was designed and evaluated with 10 healthy volunteers and three individuals with advanced amyotrophic lateral sclerosis (ALS), all of whom were given tasks to execute on the internet using the browser. Participants with ALS achieved an average accuracy of 73% and a subsequent information transfer rate (ITR) of 8.6 bits/min and healthy participants with no prior BCI experience over 90% accuracy and an ITR of 14.4 bits/min. We define additional criteria for unrestricted internet access for evaluation of the presented and future internet browsers, and we provide a review of the existing browsers in the literature. The P300-based browser provides unrestricted access and enables free web surfing for individuals with paralysis. [ABSTRACT FROM AUTHOR]

Abstract: Brain–computer interfaces (BCIs) allow a user to control a computer application by brain activity as measured, e.g., by electroencephalography (EEG). After about 30years of BCI research, the success of control that is achieved by means of a BCI system still greatly varies between subjects. For about 20% of potential users the obtained accuracy does not reach the level criterion, meaning that BCI control is not accurate enough to control an application. The determination of factors that may serve to predict BCI performance, and the development of methods to quantify a predictor value from psychological and/or physiological data serve two purposes: a better understanding of the ‘BCI-illiteracy phenomenon’, and avoidance of a costly and eventually frustrating training procedure for participants who might not obtain BCI control. Furthermore, such predictors may lead to approaches to antagonize BCI illiteracy. Here, we propose a neurophysiological predictor of BCI performance which can be determined from a two minute recording of a ‘relax with eyes open’ condition using two Laplacian EEG channels. A correlation of r =0.53 between the proposed predictor and BCI feedback performance was obtained on a large data base with N =80 BCI-naive participants in their first session with the Berlin brain–computer interface (BBCI) system which operates on modulations of sensory motor rhythms (SMRs). [Copyright &y& Elsevier]

Abstract: We propose a classical semantic conditioning procedure to allow basic yes–no communication in the completely locked-in state as an alternative to instrumental-operant learning of brain responses, which is the common approach in brain–computer interface research. More precisely, it was intended to establish cortical responses to the trueness of a statement irrespective of the particular constituent words and letters or sounds of the words. As unconditioned stimulus short aversive stimuli consisting of 1-ms electrical pulses were used. True and false statements were presented acoustically and only the true statements were immediately followed by electrical stimuli. 15 healthy participants and one locked-in ALS patient underwent the experiment. Three different classifiers were employed in order to differentiate between the two cortical responses by means of electroencephalographic recordings. The offline analysis revealed that semantic classical conditioning can be applied successfully to enable basic communication using a non-muscular channel. [Copyright &y& Elsevier]