@article{HalderHammerKleihetal.2013, author = {Halder, Sebastian and Hammer, Eva Maria and Kleih, Sonja Claudia and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Niels and K{\"u}bler, Andrea}, title = {Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude}, series = {PLoS ONE}, volume = {8}, journal = {PLoS ONE}, number = {2}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130327}, pages = {e53513}, year = {2013}, abstract = {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.}, language = {en} } @article{HalderHammerKleihetal.2013, author = {Halder, Sebastian and Hammer, Eva Maria and Kleih, Sonja Claudia and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Nils and K{\"u}bler, Andrea}, title = {Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-77992}, year = {2013}, abstract = {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.}, subject = {Psychologie}, language = {en} } @article{HalderRufFurdeaetal.2013, author = {Halder, Sebastian and Ruf, Carolin Anne and Furdea, Adrian and Pasqualotto, Emanuele and De Massari, Daniele and van der Heiden, Linda and Bogdan, Martin and Rosenstiel, Wolfgang and Birbaumer, Niels and K{\"u}bler, Andrea and Matuz, Tamara}, title = {Prediction of P300 BCI Aptitude in Severe Motor Impairment}, series = {PLoS ONE}, journal = {PLoS ONE}, doi = {10.1371/journal.pone.0076148}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-97268}, year = {2013}, abstract = {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.}, language = {en} } @article{HalderVarkutiBogdanetal.2013, author = {Halder, Sebastian and Varkuti, Balint and Bogdan, Martin and K{\"u}bler, Andrea and Rosenstiel, Wolfgang and Sitaram, Ranganatha and Birbaumer, Niels}, title = {Prediction of brain-computer interface aptitude from individual brain structure}, series = {Frontiers in Human Neuroscience}, journal = {Frontiers in Human Neuroscience}, doi = {10.3389/fnhum.2013.00105}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96558}, year = {2013}, abstract = {Objective: Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. Methods: We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Results: Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Conclusions: Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. Significance: This confirms that structural brain traits contribute to individual performance in BCI use.}, language = {en} } @article{KaethnerHalderHintermuelleretal.2017, author = {K{\"a}thner, Ivo and Halder, Sebastian and Hinterm{\"u}ller, Christoph and Espinosa, Arnau and Guger, Christoph and Miralles, Felip and Vargiu, Eloisa and Dauwalder, Stefan and Rafael-Palou, Xavier and Sol{\`a}, Marc and Daly, Jean M. and Armstrong, Elaine and Martin, Suzanne and K{\"u}bler, Andrea}, title = {A Multifunctional Brain-Computer Interface Intended for Home Use: An Evaluation with Healthy Participants and Potential End Users with Dry and Gel-Based Electrodes}, series = {Frontiers in Neuroscience}, volume = {11}, journal = {Frontiers in Neuroscience}, number = {286}, doi = {10.3389/fnins.2017.00286}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-157925}, year = {2017}, abstract = {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.}, language = {en} } @article{KaethnerKueblerHalder2015, author = {K{\"a}thner, Ivo and K{\"u}bler, Andrea and Halder, Sebastian}, title = {Comparison of eye tracking, electrooculography and an auditory brain-computer interface for binary communication: a case study with a participant in the locked-in state}, series = {Journal of NeuroEngineering and Rehabilitation}, volume = {12}, journal = {Journal of NeuroEngineering and Rehabilitation}, number = {76}, doi = {10.1186/s12984-015-0071-z}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-145305}, year = {2015}, abstract = {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.}, language = {en} } @article{KaethnerKueblerHalder2015, author = {K{\"a}thner, Ivo and K{\"u}bler, Andrea and Halder, Sebastian}, title = {Rapid P300 brain-computer interface communication with a head-mounted display}, series = {Frontiers in Neuroscience}, volume = {9}, journal = {Frontiers in Neuroscience}, number = {207}, doi = {10.3389/fnins.2015.00207}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-148520}, year = {2015}, abstract = {Visual ERP (P300) based brain-computer interfaces (BCIs) allow for fast and reliable spelling and are intended as a muscle-independent communication channel for people with severe paralysis. However, they require the presentation of visual stimuli in the field of view of the user. A head-mounted display could allow convenient presentation of visual stimuli in situations, where mounting a conventional monitor might be difficult or not feasible (e.g., at a patient's bedside). To explore if similar accuracies can be achieved with a virtual reality (VR) headset compared to a conventional flat screen monitor, we conducted an experiment with 18 healthy participants. We also evaluated it with a person in the locked-in state (LIS) to verify that usage of the headset is possible for a severely paralyzed person. Healthy participants performed online spelling with three different display methods. In one condition a 5 x 5 letter matrix was presented on a conventional 22 inch TFT monitor. Two configurations of the VR headset were tested. In the first (glasses A), the same 5 x 5 matrix filled the field of view of the user. In the second (glasses B), single letters of the matrix filled the field of view of the user. The participant in the LIS tested the VR headset on three different occasions (glasses A condition only). For healthy participants, average online spelling accuracies were 94\% (15.5 bits/min) using three flash sequences for spelling with the monitor and glasses A and 96\% (16.2 bits/min) with glasses B. In one session, the participant in the LIS reached an online spelling accuracy of 100\% (10 bits/min) using the glasses A condition. We also demonstrated that spelling with one flash sequence is possible with the VR headset for healthy users (mean: 32.1 bits/min, maximum reached by one user: 71.89 bits/min at 100\% accuracy). We conclude that the VR headset allows for rapid P300 BCI communication in healthy users and may be a suitable display option for severely paralyzed persons.}, language = {en} } @article{KueblerHolzRiccioetal.2014, author = {K{\"u}bler, Andrea and Holz, Elisa M. and Riccio, Angela and Zickler, Claudia and Kaufmann, Tobias and Kleih, Sonja C. and Staiger-S{\"a}lzer, Pit and Desideri, Lorenzo and Hoogerwerf, Evert-Jan and Mattia, Donatella}, title = {The User-Centered Design as Novel Perspective for Evaluating the Usability of BCI-Controlled Applications}, doi = {10.1371/journal.pone.0112392}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-111051}, year = {2014}, abstract = {Albeit research on brain-computer interfaces (BCI) for controlling applications has expanded tremendously, we still face a translational gap when bringing BCI to end-users. To bridge this gap, we adapted the user-centered design (UCD) to BCI research and development which implies a shift from focusing on single aspects, such as accuracy and information transfer rate (ITR), to a more holistic user experience. The UCD implements an iterative process between end-users and developers based on a valid evaluation procedure. Within the UCD framework usability of a device can be defined with regard to its effectiveness, efficiency, and satisfaction. We operationalized these aspects to evaluate BCI-controlled applications. Effectiveness was regarded equivalent to accuracy of selections and efficiency to the amount of information transferred per time unit and the effort invested (workload). Satisfaction was assessed with questionnaires and visual-analogue scales. These metrics have been successfully applied to several BCI-controlled applications for communication and entertainment, which were evaluated by end-users with severe motor impairment. Results of four studies, involving a total of N = 19 end-users revealed: effectiveness was moderate to high; efficiency in terms of ITR was low to high and workload low to medium; depending on the match between user and technology, and type of application satisfaction was moderate to high. The here suggested evaluation metrics within the framework of the UCD proved to be an applicable and informative approach to evaluate BCI controlled applications, and end-users with severe impairment and in the locked-in state were able to participate in this process.}, language = {en} } @article{MirallesVargiuDauwalderetal.2015, author = {Miralles, Felip and Vargiu, Eloisa and Dauwalder, Stefan and Sol{\`a}, Marc and M{\"u}ller-Putz, Gernot and Wriessnegger, Selina C. and Pinegger, Andreas and K{\"u}bler, Andrea and Halder, Sebastian and K{\"a}thner, Ivo and Martin, Suzanne and Daly, Jean and Armstrong, Elaine and Guger, Christoph and Hinterm{\"u}ller, Christoph and Lowish, Hannah}, title = {Brain computer interface on track to home.}, series = {The Scientific World Journal}, volume = {2015}, journal = {The Scientific World Journal}, number = {623896}, doi = {10.1155/2015/623896}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-149575}, year = {2015}, abstract = {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.}, language = {en} } @article{SimonKaethnerRufetal.2015, author = {Simon, Nadine and K{\"a}thner, Ivo and Ruf, Carolin A. and Pasqualotto, Emanuele and K{\"u}bler, Andrea and Halder, Sebastian}, title = {An auditory multiclass brain-computer interface with natural stimuli: Usability evaluation with healthy participants and a motor impaired end user}, series = {Frontiers in Human Neuroscience}, volume = {8}, journal = {Frontiers in Human Neuroscience}, number = {1039}, doi = {10.3389/fnhum.2014.01039}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-126450}, year = {2015}, abstract = {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.}, language = {en} }