Elisa Mira Holz

A Brain-Computer Interface as Input Channel for a Standard Assistive Technology Software

Recently brain-computer interface (BCI) control was integrated into the commercial assistive technology product QualiWORLD (QualiLife Inc., Paradiso-Lugano, CH). Usability of the first prototype was evaluated in terms of effectiveness (accuracy), efficiency (information transfer rate and subjective workload/NASA Task Load Index) and user satisfaction (Quebec User Evaluation of Satisfaction with assistive Technology, QUEST 2.0) by four end-users with severe disabilities. Three assistive technology experts evaluated the device from a third person perspective. The results revealed high performance levels in communication and internet tasks. Users and assistive technology experts were quite satisfied with the device. However, none could imagine using the device in daily life without improvements. Main obstacles were the EEG-cap and low speed.

Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state

This paper describes a case study with a patient in the classic locked-in state, who currently has no means of independent communication. Following a user-centered approach, we investigated event-related potentials (ERP) elicited in different modalities for use in brain-computer interface (BCI) systems. Such systems could provide her with an alternative communication channel. To investigate the most viable modality for achieving BCI based communication, classic oddball paradigms (1 rare and 1 frequent stimulus, ratio 1:5) in the visual, auditory and tactile modality were conducted (2 runs per modality). Classifiers were built on one run and tested offline on another run (and vice versa). In these paradigms, the tactile modality was clearly superior to other modalities, displaying high offline accuracy even when classification was performed on single trials only. Consequently, we tested the tactile paradigm online and the patient successfully selected targets without any error. Furthermore, we investigated use of the visual or tactile modality for different BCI systems with more than two selection options. In the visual modality, several BCI paradigms were tested offline. Neither matrix-based nor so-called gaze-independent paradigms constituted a means of control. These results may thus question the gaze-independence of current gaze-independent approaches to BCI. A tactile four-choice BCI resulted in high offline classification accuracies. Yet, online use raised various issues. Although performance was clearly above chance, practical daily life use appeared unlikely when compared to other communication approaches (e.g., partner scanning). Our results emphasize the need for user-centered design in BCI development including identification of the best stimulus modality for a particular user. Finally, the paper discusses feasibility of EEG-based BCI systems for patients in classic locked-in state and compares BCI to other AT solutions that we also tested during the study.

The user-centered design as novel perspective for evaluating the usability of BCI-controlled applications.

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.

Motor imagery for severely motor-impaired patients: evidence for brain-computer interfacing as superior control solution.

Brain-Computer Interfaces (BCIs) strive to decode brain signals into control commands for severely handicapped people with no means of muscular control. These potential users of noninvasive BCIs display a large range of physical and mental conditions. Prior studies have shown the general applicability of BCI with patients, with the conflict of either using many training sessions or studying only moderately restricted patients. We present a BCI system designed to establish external control for severely motor-impaired patients within a very short time. Within only six experimental sessions, three out of four patients were able to gain significant control over the BCI, which was based on motor imagery or attempted execution. For the most affected patient, we found evidence that the BCI could outperform the best assistive technology (AT) of the patient in terms of control accuracy, reaction time and information transfer rate. We credit this success to the applied user-centered design approach and to a highly flexible technical setup. State-of-the art machine learning methods allowed the exploitation and combination of multiple relevant features contained in the EEG, which rapidly enabled the patients to gain substantial BCI control. Thus, we could show the feasibility of a flexible and tailorable BCI application in severely disabled users. This can be considered a significant success for two reasons: Firstly, the results were obtained within a short period of time, matching the tight clinical requirements. Secondly, the participating patients showed, compared to most other studies, very severe communication deficits. They were dependent on everyday use of AT and two patients were in a locked-in state. For the most affected patient a reliable communication was rarely possible with existing AT.

A User Centred Approach for Bringing BCI Controlled Applications to End-Users

In the past 20 years research on BCI has been increasing almost exponentially. While a great deal of experimentation was dedicated to offline analysis for improving signal detection and translation, online studies with the target population are less common. Although BCIs are also developed for entertainment and thus potentially for healthy users, the main focus for BCI applications that are aiming at communication and control are people with severe motor impairment. There is a great need for translational studies that test BCI at home with the target population. Further, long-term studies with users in the field are required to improve reliability of BCI control. The user centred approach appears suitable to foster such studies.

Toward Independent Home Use of Brain-Computer Interfaces: A Decision Algorithm for Selection of Potential End-Users

Noninvasive brain-computer interfaces (BCIs) use scalp-recorded electrical activity from the brain to control an application. Over the past 20 years, research demonstrating that BCIs can provide communication and control to individuals with severe motor impairment has increased almost exponentially. Although considerable effort has been dedicated to offline analysis for improving signal detection and translation, far less effort has been made to conduct online studies with target populations. Thus, there remains a great need for both long-term and translational BCI studies that include individuals with disabilities in their own homes. Completing these studies is the only sure means to answer questions about BCI utility and reliability. Here we suggest an algorithm for candidate selection for electroencephalographic (EEG)-based BCI home studies. This algorithm takes into account BCI end-users and their environment and should assist in study design and substantially improve subject retention rates, thereby improving the overall efficacy of BCI home studies. It is the result of a workshop at the Fifth International BCI Meeting that allowed us to leverage the expertise of multiple research laboratories and people from multiple backgrounds in BCI research.

User Centred Design in BCI Development

Development of assistive solutions for people with disabilities clearly benefits from the full involvement of potential users in all stages of the development cycle. In this chapter we will discuss different aspects of user involvement and the role that users could or should have in the design and development of BCI driven assistive applications. We will focus on BCI applications in the field of communication, access to ICT and environmental control, typical areas where AT solutions can make the difference between participation or exclusion.

Neural correlates of visuo-spatial working memory encoding-An EEG study.

The aim of the present electroencephalographic (EEG) study was to investigate neuronal correlates of working memory encoding in a visuo-spatial serial delayed match-to-sample task. A rapid serial visual presentation approach was used to dissociate brain activity related to encoding of visuo-spatial targets and cortical activity evoked by suppression of distracting information. During the task EEG was recorded and steady-state visually evoked potentials (SSVEPs) were calculated. Finally, standardized low-resolution electromagnetic tomography (sLORETA) was used to determine brain regions involved in visuo-spatial working memory encoding. A distributed task-relevant network comprising right temporal, parietal, and occipital areas was identified. Results suggest that activity of this network is amplified during actual encoding of targets into visual working memory, whereas the same network is attenuated in its activation when distracting visual information should be suppressed. Left prefrontal and anterior cingulate cortices do not seem to be involved in encoding of targets but only in suppression of distracting information, likely reflecting activity of an attention-based supervisory system. These results strongly emphasise the linkage between visuo-spatial attention and working memory during amplification of selected and suppression of irrelevant information.

Applying the user-centred design to evaluation of Brain-Computer Interface controlled applications

In recent years different applications have been linked to BCI control and tested by severely motor impaired users in the field. An effort has been made to apply objective and standardised evaluation metrics to foster a user-centred design process in the development of BCI controlled applications. The user-centred design appears appropriate to bridge the reliability and translational gap faced by BCI research that aims at providing people in need with an optimally adapted assistive BCI driven technology.

Using Brain Painting at Home for 5 Years: Stability of the P300 During Prolonged BCI Usage by Two End-Users with ALS

Brain painting (BP) is non-invasive electroencephalography (EEG) based Brain-Computer Interface (BCI) for creative expression based on a P300 matrix. The technology was transferred into a home setup for two patients with amyotrophic lateral sclerosis (ALS), who used the system for several years while being evaluated on performance and satisfaction. Holz and colleagues found that the use of BP increased quality of life. Additionally, they described that changes in the amplitude of the P300 ERPs could be observed between recalibrations of the BCI. In this paper, we quantified the evolution of the P300 peaks in the two BCI end-users (HP and JT). For HP, the P300 peak amplitude increased during 9 months, then progressively decreased for the following 51 months, but the BCI accuracy remained stable. JT’s P300 peak amplitude did not significantly decrease during 32 months that separated the calibrations. Yet, JT’s BCI accuracy declined which we may attribute to a decline in physical functioning due to ALS. Painters used online BCI for hundreds of hours (HP 755, JT 223) and both finished more than 50 named brain paintings. HP could use BP autonomously and regularly at home for 33 months without recalibration of the system, and JT for 10 months, suggesting the stability of P300 and SWLDA online classifiers in the long-term, and demonstrating the feasibility of having a P300 based system at home that requires few involvement of BCI experts.