@phdthesis{Leinfelder2022, author = {Leinfelder, Teresa}, title = {Untersuchung von Trainingseffekten bei der Verwendung einer auditorischen P300-basierten EEG Gehirn-Computer Schnittstelle mittels fMRI Analyse}, doi = {10.25972/OPUS-29068}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-290683}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2022}, abstract = {In dieser Dissertation untersuchten wir die neuronalen Korrelate des Training-Effektes einer auditorischen P300 Gehirn-Computer Schnittstelle mittels fMRI Analyse in einem pr{\"a}-post Design mit zehn gesunden Testpersonen. Wir wiesen in drei Trainings-sitzungen einen Trainingseffekt in der EEG-Analyse der P300 Welle nach und fanden entsprechende Kontraste in einer pr{\"a}-post Analyse von fMRI Daten, wobei in allen f{\"u}nf Sitzungen das gleiche Paradigma verwendet wurde. In der fMRI Analyse fanden wir fol-gende Ergebnisse: in einem Target-/ Nichttarget Kontrast zeigte sich verst{\"a}rkte Aktivie-rung in Generatorregionen der P300 Welle (temporale und inferiore frontale Regionen) und interessanterweise auch in motorassoziierten Arealen, was h{\"o}here kognitiver Pro-zesse wie Aufmerksamkeitslenkung und Arbeitsspeicher widerspiegeln k{\"o}nnte. Der Kon-trast des Trainingseffektes zeigte nach dem Training einen st{\"a}rkeren Rebound Effekt im Sinne einer verst{\"a}rkten Aktivierung in Generatorregionen der P300 Welle, was eine ver-besserte Erkennung und Prozessierung von Target-Stimuli reflektieren k{\"o}nnte. Eine Ab-nahme von Aktivierung in frontalen Arealen in diesem Kontrast k{\"o}nnte durch effizientere Abl{\"a}ufe kognitiver Prozesse und des Arbeitsged{\"a}chtnis erkl{\"a}rt werden.}, subject = {Gehirn-Computer-Schnittstelle}, language = {de} } @phdthesis{Eidel2020, author = {Eidel, Matthias T. A. M.}, title = {Training Effects of a Tactile Brain-Computer Interface System During Prolonged Use by Healthy And Motor-Impaired People}, doi = {10.25972/OPUS-20851}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-208511}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2020}, abstract = {Background - Brain-Computer Interfaces (BCI) enable their users to interact and communicate with the environment without requiring intact muscle control. To this end, brain activity is directly measured, digitized and interpreted by the computer. Thus, BCIs may be a valuable tool to assist severely or even completely paralysed patients. Many BCIs, however, rely on neurophysiological potentials evoked by visual stimulation, which can result in usability issues among patients with impaired vision or gaze control. Because of this, several non-visual BCI paradigms have been developed. Most notably, a recent study revealed promising results from a tactile BCI for wheelchair control. In this multi-session approach, healthy participants used the BCI to navigate a simulated wheelchair through a virtual apartment, which revealed not only that the BCI could be operated highly efficiently, but also that it could be trained over five sessions. The present thesis continues the research on this paradigm in order to - confirm its previously reported high performance levels and trainability - reveal the underlying factors responsible for observed performance increases - establish its feasibility among potential impaired end-users Methods - To approach these goals, three studies were conducted with both healthy participants and patients with amyotrophic lateral sclerosis (ALS). Brain activity during BCI operation was recorded via electroencephalography (EEG) and interpreted using a machine learning-based linear classifier. Wheelchair navigation was executed according to the classification results and visualized on a monitor. For offline statistical analysis, neurophysiological features were extracted from EEG data. Subjective data on usability were collected from all participants. Two specialized experiments were conducted to identify factors for training. Results and Discussion - Healthy participants: Results revealed positive effects of training on BCI performances and their underlying neurophysiological potentials. The paradigm was confirmed to be feasible and (for a non-visual BCI) highly efficient for most participants. However, some had to be excluded from analysis of the training effects because they could not achieve meaningful BCI control. Increased somatosensory sensitivity was identified as a possible mediator for training-related performance improvements. Participants with ALS: Out of seven patients with various stages of ALS, five could operate the BCI with accuracies significantly above chance level. Another ALS patient in a state of near-complete paralysis trained with the BCI for several months. Although no effects of training were observed, he was consistently able to operate the system above chance level. Subjective data regarding workload, satisfaction and other parameters were reported. Significance - The tactile BCI was evaluated on the example of wheelchair control. In the future, it could help impaired patients to regain some lost mobility and self-sufficiency. Further, it has the potential to be adapted to other purposes, including communication. Once visual BCIs and other assistive technologies fail for patients with (progressive) motor impairments, vision-independent paradigms such as the tactile BCI may be among the last remaining alternatives to interact with the environment. The present thesis has strongly confirmed the general feasibility of the tactile paradigm for healthy participants and provides first clues about the underlying factors of training. More importantly, the BCI was established among potential end-users with ALS, providing essential external validity.}, subject = {Myatrophische Lateralsklerose}, language = {en} } @phdthesis{Holz2015, author = {Holz, Elisa Mira}, title = {Systematic evaluation of non-invasive brain-computer interfaces as assistive devices for persons with severe motor impairment based on a user-centred approach - in controlled settings and independent use}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-126334}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2015}, abstract = {Brain-computer interfaces (BCIs) are devices that translate signals from the brain into control commands for applications. Within the last twenty years, BCI applications have been developed for communication, environmental control, entertainment, and substitution of motor functions. Since BCIs provide muscle independent communication and control of the environment by circumventing motor pathways, they are considered as assistive technologies for persons with neurological and neurodegenerative diseases leading to motor paralysis, such as amyotrophic lateral sclerosis (ALS), muscular dystrophy, spinal muscular atrophy and stroke (K{\"u}bler, Kotchoubey, Kaiser, Wolpaw, \& Birbaumer, 2001). Although most researcher mention persons with severe motor impairment as target group for their BCI systems, most studies include healthy participants and studies including potential BCI end-users are sparse. Thus, there is a substantial lack of studies that investigate whether results obtained in healthy participants can be transferred to patients with neurodegenerative diseases. This clearly shows that BCI research faces a translational gap between intense BCI research and bringing BCI applications to end-users outside the lab (K{\"u}bler, Mattia, Rupp, \& Tangermann, 2013). Translational studies are needed that investigate whether BCIs can be successfully used by severely disabled end-users and whether those end-users would accept BCIs as assistive devices. Another obvious discrepancy exists between a plethora of short-term studies and a sparse number of long-term studies. BCI research thus also faces a reliability gap (K{\"u}bler, Mattia, et al., 2013). Most studies present only one BCI session, however the few studies that include several testing sessions indicate high inter- and intra-individual variance in the end-users' performance due to non-stationarity of signals. Long-term studies, however, are needed to demonstrate whether a BCI can be reliably used as assistive device over a longer period of time in the daily-life of a person. Therefore there is also a great need for reliability studies. The purpose of the present thesis was to address these research gaps and to bring BCIs closer to end-users in need, especially into their daily-lives, following a user-centred design (UCD). The UCD was suggested as theoretical framework for bringing BCIs to end-users by K{\"u}bler and colleagues (K{\"u}bler et al., 2014; Zickler et al., 2011). This approach aims at the close and iterative interaction between BCI developers and end-users with the final goal to develop BCI systems that are accepted as assistive devices by end-users. The UCD focuses on usability, that is, how well a BCI technology matches the purpose and meets the needs and requirements of the targeted end-users and was standardized with the ISO 9241-210. Within the UCD framework, usability of a device can be defined with regard to its effectiveness, efficiency and satisfaction. These aspects were operationalized by K{\"u}bler and colleagues to evaluate BCI-controlled applications. As suggested by Vaughan and colleagues, the number of BCI sessions, the total usage duration and the impact of the BCI on the life of the person can be considered as indicators of usefulness of the BCI in long-term daily-life use (Vaughan, Sellers, \& Wolpaw, 2012). These definitions and metrics for usability and usefulness were applied for evaluating BCI applications as assistive devices in controlled settings and independent use. Three different BCI applications were tested and evaluated by in total N=10 end-users: In study 1 a motor-imagery (MI) based BCI for gaming was tested by four end-users with severe motor impairment. In study 2, a hybrid P300 event-related (ERP) based BCI for communication was tested by four severely motor restricted end-users with severe motor impairment. Study 1 and 2 are short-term studies conducted in a controlled-setting. In study 3 a P300-ERP BCI for creative expression was installed for long-term independent use at the homes of two end-users in the locked-in state. Both end-users are artists who had gradually lost the ability to paint after being diagnosed with ALS. Results reveal that BCI controlled devices are accepted as assistive devices. Main obstacles for daily-life use were the not very aesthetic design of the EEG-cap and electrodes (cap is eye-catching and looks medical), low comfort (cables disturb, immobility, electrodes press against head if lying on a head cushion), complicated and time-consuming adjustment, low efficiency and low effectiveness, and not very high reliability (many influencing factors). While effectiveness and efficiency in the MI based BCI were lower compared to applications using the P300-ERP as input channel, the MI controlled gaming application was nevertheless better accepted by the end-users and end-users would rather like to use it compared to the communication applications. Thus, malfunctioning and errors, low speed, and the EEG cap are rather tolerated in gaming applications, compared to communication devices. Since communication is essential for daily-life, it has to be fast and reliable. BCIs for communication, at the current state of the art, are not considered competitive with other assistive devices, if other devices, such as eye-gaze, are still an option. However BCIs might be an option when controlling an application for entertainment in daily-life, if communication is still available. Results demonstrate that BCI is adopted in daily-life if it matches the end-users needs and requirements. Brain Painting serves as best representative, as it matches the artists' need for creative expression. Caveats such as uncomfortable cap, dependence on others for set-up, and experienced low control are tolerated and do not prevent BCI use on a daily basis. Also end-users in real need of means for communication, such as persons in the locked-in state with unreliable eye-movement or no means for independent communication, do accept obstacles of the BCI, as it is the last or only solution to communicate or control devices. Thus, these aspects are "no real obstacles" but rather "challenges" that do not prevent end-users to use the BCI in their daily-lives. For instance, one end-user, who uses a BCI in her daily-life, stated: "I don't care about aesthetic design of EEG cap and electrodes nor amplifier". Thus, the question is not which system is superior to the other, but which system is best for an individual user with specific symptoms, needs, requirements, existing assistive solutions, support by caregivers/family etc.; it is thereby a question of indication. These factors seem to be better "predictors" for adoption of a BCI in daily-life, than common usability criterions such as effectiveness or efficiency. The face valid measures of daily-life demonstrate that BCI-controlled applications can be used in daily-life for more than 3 years, with high satisfaction for the end-users, without experts being present and despite a decrease in the amplitude of the P300 signal. Brain Painting re-enabled both artists to be creatively active in their home environment and thus improved their feelings of happiness, usefulness, self-esteem, well-being, and consequently quality of life and supports social inclusion. This thesis suggests that BCIs are valuable tools for people in the locked-in state.}, subject = {Gehirn-Computer-Schnittstelle}, language = {en} } @phdthesis{Sollfrank2015, author = {Sollfrank, Teresa}, title = {Feedback efficiency and training effects during alpha band modulation over the sensorimotor cortex}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-131769}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2015}, abstract = {Neural oscillations can be measured by electroencephalography (EEG) and these oscillations can be characterized by their frequency, amplitude and phase. The mechanistic properties of neural oscillations and their synchronization are able to explain various aspects of many cognitive functions such as motor control, memory, attention, information transfer across brain regions, segmentation of the sensory input and perception (Arnal and Giraud, 2012). The alpha band frequency is the dominant oscillation in the human brain. This oscillatory activity is found in the scalp EEG at frequencies around 8-13 Hz in all healthy adults (Makeig et al., 2002) and considerable interest has been generated in exploring EEG alpha oscillations with regard to their role in cognitive (Klimesch et al., 1993; Hanselmayr et al., 2005), sensorimotor (Birbaumer, 2006; Sauseng et al., 2009) and physiological (Lehmann, 1971; Niedermeyer, 1997; Kiyatkin, 2010) aspects of human life. The ability to voluntarily regulate the alpha amplitude can be learned with neurofeedback training and offers the possibility to control a brain-computer interface (BCI), a muscle independent interaction channel. BCI research is predominantly focused on the signal processing, the classification and the algorithms necessary to translate brain signals into control commands than on the person interacting with the technical system. The end-user must be properly trained to be able to successfully use the BCI and factors such as task instructions, training, and especially feedback can therefore play an important role in learning to control a BCI (Neumann and K{\"u}bler, 2003; Pfurtscheller et al., 2006, 2007; Allison and Neuper, 2010; Friedrich et al., 2012; Kaufmann et al., 2013; Lotte et al., 2013). The main purpose of this thesis was to investigate how end-users can efficiently be trained to perform alpha band modulation recorded over their sensorimotor cortex. The herein presented work comprises three studies with healthy participants and participants with schizophrenia focusing on the effects of feedback and training time on cortical activation patterns and performance. In the first study, the application of a realistic visual feedback to support end-users in developing a concrete feeling of kinesthetic motor imagery was tested in 2D and 3D visualization modality during a single training session. Participants were able to elicit the typical event-related desynchronisation responses over sensorimotor cortex in both conditions but the most significant decrease in the alpha band power was obtained following the three-dimensional realistic visualization. The second study strengthen the hypothesis that an enriched visual feedback with information about the quality of the input signal supports an easier approach for motor imagery based BCI control and can help to enhance performance. Significantly better performance levels were measurable during five online training sessions in the groups with enriched feedback as compared to a conventional simple visual feedback group, without significant differences in performance between the unimodal (visual) and multimodal (auditory-visual) feedback modality. Furthermore, the last study, in which people with schizophrenia participated in multiple sessions with simple feedback, demonstrated that these patients can learn to voluntarily regulate their alpha band. Compared to the healthy group they required longer training times and could not achieve performance levels as high as the control group. Nonetheless, alpha neurofeedback training lead to a constant increase of the alpha resting power across all 20 training session. To date only little is known about the effects of feedback and training time on BCI performance and cortical activation patterns. The presented work contributes to the evidence that healthy individuals can benefit from enriched feedback: A realistic presentation can support participants in getting a concrete feeling of motor imagery and enriched feedback, which instructs participants about the quality of their input signal can give support while learning to control the BCI. This thesis demonstrates that people with schizophrenia can learn to gain control of their alpha oscillations recorded over the sensorimotor cortex when participating in sufficient training sessions. In conclusion, this thesis improved current motor imagery BCI feedback protocols and enhanced our understanding of the interplay between feedback and BCI performance.}, subject = {Neurofeedback}, language = {en} } @phdthesis{Kaufmann2013, author = {Kaufmann, Tobias}, title = {Brain-computer interfaces based on event-related potentials: toward fast, reliable and easy-to-use communication systems for people with neurodegenerative disease}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-83441}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2013}, abstract = {Objective: Brain Computer Interfaces (BCI) provide a muscle independent interaction channel making them particularly valuable for individuals with severe motor impairment. Thus, different BCI systems and applications have been proposed as assistive technology (AT) solutions for such patients. The most prominent system for communication utilizes event-related potentials (ERP) obtained from the electroencephalogram (EEG) to allow for communication on a character-by-character basis. Yet in their current state of technology, daily life use cases of such systems are rare. In addition to the high EEG preparation effort, one of the main reasons is the low information throughput compared to other existing AT solutions. Furthermore, when testing BCI systems in patients, a performance drop is usually observed compared to healthy users. Patients often display a low signal-to-noise ratio of the recorded EEG and detection of brain responses may be aggravated due to internally (e.g. spasm) or externally induced artifacts (e.g. from ventilation devices). Consequently, practical BCI systems need to cope with mani-fold inter-individual differences. Whilst these high demands lead to increasing complexity of the technology, daily life use of BCI systems requires straightforward setup including an easy-to-use graphical user interface that nonprofessionals can handle without expert support. Research questions of this thesis: This dissertation project aimed at bringing forward BCI technology toward a possible integration into end-users' daily life. Four basic research questions were addressed: (1) Can we identify performance predictors so that we can provide users with individual BCI solutions without the need of multiple, demanding testing sessions? (2) Can we provide complex BCI technology in an automated, user-friendly and easy-to-use manner, so that BCIs can be used without expert support at end-users' homes? (3) How can we account for and improve the low information transfer rates as compared to other existing assistive technology solutions? (4) How can we prevent the performance drop often seen when bringing BCI technology that was tested in healthy users to those with severe motor impairment? Results and discussion: (1) Heart rate variability (HRV) as an index of inhibitory control (i.e. the ability to allocate attention resources and inhibit distracting stimuli) was significantly related to ERP-BCI performance and accounted for almost 26\% of variance. HRV is easy to assess from short heartbeat recordings and may thus serve as a performance predictor for ERP-BCIs. Due to missing software solutions for appropriate processing of artifacts in heartbeat data (electrocardiogram and inter-beat interval data), our own tool was developed that is available free of charge. To date, more than 100 researchers worldwide have requested the tool. Recently, a new version was developed and released together with a website (www.artiifact.de). (2) Furthermore, a study of this thesis demonstrated that BCI technology can be incorporated into easy-to-use software, including auto-calibration and predictive text entry. Na{\"i}ve, healthy nonprofessionals were able to control the software without expert support and successfully spelled words using the auto-calibrated BCI. They reported that software handling was straightforward and that they would be able to explain the system to others. However, future research is required to study transfer of the results to patient samples. (3) The commonly used ERP-BCI paradigm was significantly improved. Instead of simply highlighting visually displayed characters as is usually done, pictures of famous faces were used as stimulus material. As a result, specific brain potentials involved in face recognition and face processing were elicited. The event-related EEG thus displayed an increased signal-to-noise ratio, which facilitated the detection of ERPs extremely well. Consequently, BCI performance was significantly increased. (4) The good results of this new face-flashing paradigm achieved with healthy participants transferred well to users with neurodegenerative disease. Using a face paradigm boosted information throughput. Importantly, two users who were highly inefficient with the commonly used paradigm displayed high accuracy when exposed to the face paradigm. The increased signal-to-noise ratio of the recorded EEG thus helped them to overcome their BCI inefficiency. Significance: The presented work at hand (1) successfully identified a physiological predictor of ERP-BCI performance, (2) proved the technology ready to be operated by na{\"i}ve nonprofessionals without expert support, (3) significantly improved the commonly used spelling paradigm and (4) thereby displayed a way to effectively prevent BCI inefficiency in patients with neurodegenerative disease. Additionally, missing software solutions for appropriate handling of artifacts in heartbeat data encouraged development of our own software tool that is available to the research community free of charge. In sum, this thesis significantly improved current BCI technology and enhanced our understanding of physiological correlates of BCI performance.}, subject = {Gehirn-Computer-Schnittstelle}, language = {en} } @phdthesis{Botrel2018, author = {Botrel, Loic}, title = {Brain-computer interfaces (BCIs) based on sensorimotor rhythms - Evaluating practical interventions to improve their performance and reduce BCI inefficiency}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-168110}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2018}, abstract = {Brain computer interfaces based on sensorimotor rhythms modulation (SMR-BCIs) allow people to emit commands to an interface by imagining right hand, left hand or feet movements. The neurophysiological activation associated with those specific mental imageries can be measured by electroencephalography and detected by machine learning algorithms. Improvements for SMR-BCI accuracy in the last 30 years seem to have reached a limit. The currrent main issue with SMR-BCIs is that between 15\% to 30\% cannot use the BCI, called the "BCI inefficiency" issue. Alternatively to hardware and software improvements, investigating the individual characteristics of the BCI users has became an interesting approach to overcome BCI inefficiency. In this dissertation, I reviewed existing literature concerning the individual sources of variation in SMR-BCI accuracy and identified generic individual characteristics. In the empirical investigation, attention and motor dexterity predictors for SMR-BCI performance were implemented into a trainings that would manipulate those predictors and lead to higher SMR-BCI accuracy. Those predictors were identified by Hammer et al. (2012) as the ability to concentrate (associated with relaxation levels) and "mean error duration" in a two-hand visuo-motor coordination task (VMC). Prior to a SMR-BCI session, a total of n=154 participants in two locations took part of 23 min sessions of either Jacobson's Progressive Muscle Relaxation session (PMR), a VMC session, or a control group (CG). No effect of PMR or VMC manipulation was found, but the manipulation checks did not consistently confirm whether PMR had an effect of relaxation levels and VMC on "mean error duration". In this first study, correlations between relaxation levels or "mean error duration" and accuracy were found but not in both locations. A second study, involving n=39 participants intensified the training in four sessions on four consecutive days or either PMR, VMC or CG. The effect or manipulation was assessed for in terms of a causal relationship by using a PRE-POST study design. The manipulation checks of this second study validated the positive effect of training on both relaxation and "mean error duration". But the manipulation did not yield a specific effect on BCI accuracy. The predictors were not found again, displaying the instability of relaxation levels and "mean error duration" in being associated with BCI performance. An effect of time on BCI accuracy was found, and a correlation between State Mindfulness Scale and accuracy were reported. Results indicated that a short training of PMR or VMC were insufficient in increasing SMR-BCI accuracy. This study contrasted with studies succeeding in increasing SMR-BCI accuracy Tan et al. (2009, 2014), by the shortness of its training and the relaxation training that did not include mindfulness. It also contrasted by its manipulation checks and its comprehensive experimental approach that attempted to replicate existing predictors or correlates for SMR-BCI accuracy. The prediction of BCI accuracy by individual characteristics is receiving increased attention, but requires replication studies and a comprehensive approach, to contribute to the growing base of evidence of predictors for SMR-BCI accuracy. While short PMR and VMC trainings could not yield an effect on BCI performance, mindfulness meditation training might be beneficial for SMR-BCI accuracy. Moreover, it could be implemented for people in the locked-in-syndrome, allowing to reach the end-users that are the most in need for improvements in BCI performance.}, subject = {Gehirn-Computer-Schnittstelle}, language = {en} } @phdthesis{Herweg2016, author = {Herweg, Andreas}, title = {Beyond the state of the art, towards intuitive and reliable non-visual Brain-Computer-Interfacing}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-133447}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2016}, abstract = {For the present work three main goals were formulated: goal 1 To design a tactile BCI used for mobility which is intuitive (G1.1), reliable and fast while being usable by participants aged 50 years and above. goal 2 To design an auditory BCI used for communication which is intuitive and reliable. goal 3 To examine the effects of training on tactile and auditory BCI performance. Three studies were performed to achieve these goals. In the first study nine participants aged above 50 years performed a five-session training after which eight participants were able to navigate a virtual wheelchair with mean accuracy above 95\% and an ITR above 20 bits / min. In the second study 15 participants, four of them endusers with motor-impairment, were able to communicate meaningful with high accuracies using an auditory BCI. In the third study nine healthy and nine visually impaired participants (regarded as sensory experts for non-visual perception) performed tactile, auditory and visual (for healthy participants only) copy tasks. Participants with trained perception significantly outperformed control participants for tactile but not for auditory performance. Tactile performance of sensory experts was on equal levels as the visual performance of control participants. We were able to demonstrate viability of intuitive gazeindependent tactile and auditory BCI. Our tactile BCI performed on levels similar to those of visual BCI, outperforming current tactile BCI protocols. Furthermore, we were able to demonstrate significant beneficial effect of training on tactile BCI performance. Our results demonstrate previously untapped potential for tactile BCI and avenues for future research in the field of gaze-independent BCI.}, subject = {Gehirn-Computer-Schnittstelle}, language = {en} }