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Brain computer interfaces (BCIs) allow for controlling devices through modulation of sensorimotor rhythms (SMR), yet a profound number of users is unable to achieve sufficient accuracy. Here, we investigated if visuo-motor coordination (VMC) training or Jacobsen's progressive muscle relaxation (PMR) prior to BCI use would increase later performance compared to a control group who performed a reading task (CG). Running the study in two different BCI-labs, we achieved a joint sample size of N = 154 naive participants. No significant effect of either intervention (VMC, PMR, control) was found on resulting BCI performance. Relaxation level and visuo-motor performance were associated with later BCI performance in one BCI-lab but not in the other. These mixed results do not indicate a strong potential of VMC or PMR for boosting performance. Yet further research with different training parameters or experimental designs is needed to complete the picture.

Objective A Brain Computer Interface (BCI) speller is a communication device, which can be used by patients suffering from neurodegenerative diseases to select symbols in a computer application. For patients unable to overtly fixate the target symbol, it is crucial to develop a speller independent of gaze shifts. In the present online study, we investigated rapid serial visual presentation (RSVP) as a paradigm for mental typewriting. Methods We investigated the RSVP speller in three conditions, regarding the Stimulus Onset Asynchrony (SOA) and the use of color features. A vocabulary of 30 symbols was presented one-by-one in a pseudo random sequence at the same location of display. Results All twelve participants were able to successfully operate the RSVP speller. The results show a mean online spelling rate of 1.43 symb/min and a mean symbol selection accuracy of 94.8% in the best condition. Conclusion We conclude that the RSVP is a promising paradigm for BCI spelling and its performance is competitive with the fastest gaze-independent spellers in literature. Significance The RSVP speller does not require gaze shifts towards different target locations and can be operated by non-spatial visual attention, therefore it can be considered as a valid paradigm in applications with patients for impaired oculo-motor control.

Current trends and needs in Human-Computer Interaction (HCI) are rapidly increasing; however the possibility to estimate user's state remains unchanged. The need to predict user's state and intentions, and to adapt accordingly in real time to her/his decisions could bring benefits in this dual interaction. Following this purpose, we evaluate the state of a user by means of cognitive processing. In this way, we study the feasibility of detecting the level of cognitive processing, in order to be used for controlling or modifying the interface of a HCI application, such as, an information seeking application. We study this feasibility by analyzing the event-related spectral perturbations evoked by two levels of cognitive processing.

An approach to the neural measurement of perceived image quality using electroencephalography (EEG) is presented. 6 different images were tested on 6 different distortion levels. The distortions were introduced by a hybrid video encoder. The presented study consists of two parts: In a first part, subjects were asked to evaluate the quality of the test stimuli behaviorally during a conventional psychophysical test using a degradation category rating procedure. In a second part, subjects were presented undistorted and distorted texture images in a periodically alternating fashion at a fixed frequency. This alternating presentation elicits so called steady-state visual evoked potentials (SSVEP) as a brain response that can be measured on the scalp. The amplitude of modulations in the brain signals is significantly and strongly negatively correlated with the magnitude of visual impairment reported by the subjects. This neurophysiological approach to image quality assessment may potentially lead to a more objective evaluation, as behavioral approaches suffer from drawbacks such as biases, inter-subject variances and limitations to test duration.

Brain Computer Interfaces (BCIs) can be used as communication devices for people affected by neurodegenerative diseases like Amyotrophic Lateral Sclerosis (ALS). The progressive motor-control impairment caused by ALS motivates the development of BCI paradigms that do not rely on eye movement. In the present study, we investigated the feasibility of the first truly gaze-independent visual BCI, called Chroma Speller. Stimuli consist of colors displayed widescreen, which make the focus of gaze irrelevant to the BCI-spelling. The speller was tested online with 9 healthy participants. Mean online symbol-selection accuracy of 88.4% and mean online spelling speed of 1.4 char/min were achieved, using 5 repetitions of the stimuli. These results demonstrate that the abstract association between colors and symbols does not compromise the usability of the speller, leading to performances competitive with the most recent gaze-independent spellers in literature.

An event-related potential (ERP) speller is a brain computer interface (BCI) based on the detection on ERPs that can be used as spelling device for those people deprived of other means of communication. In the present online study we investigated in twelve participants the performance of an ERP speller based on the rapid serial visual presentation paradigm (RSVP). Three variants of the RSVP speller have been investigated regarding chromaticism and speed of stimulus presentation. All the subjects were able to successfully operate the RSVP speller and high mean symbol selection accuracies were reached in all conditions, (93.6% to 94.8%). Offline analysis revealed a possible mean spelling speed of about 2 symb/min for an optimized number of stimulus sequences. The RSVP speller is intuitive to use and it is gaze independent, which makes it suitable for patients with deterioration of oculomotor control.

Most present-day visual brain computer interfaces (BCIs) suffer from the fact that they rely on eye movements, are slow-paced, or feature a small vocabulary. As a potential remedy, we explored a novel BCI paradigm consisting of a central rapid serial visual presentation (RSVP) of the stimuli. It has a large vocabulary and realizes a BCI system based on covert non-spatial selective visual attention. In an offline study, eight participants were presented sequences of rapid bursts of symbols. Two different speeds and two different color conditions were investigated. Robust early visual and P300 components were elicited time-locked to the presentation of the target. Offline classification revealed a mean accuracy of up to 90% for selecting the correct symbol out of 30 possibilities. The results suggest that RSVP-BCI is a promising new paradigm, also for patients with oculomotor impairments.

Objective. Recent studies exploit the neural signal recorded via electroencephalography (EEG) to get a more objective measurement of perceived video quality. Most of these studies capitalize on the event-related potential component P3. We follow an alternative approach to the measurement problem investigating steady state visual evoked potentials (SSVEPs) as EEG correlates of quality changes. Unlike the P3, SSVEPs are directly linked to the sensory processing of the stimuli and do not require long experimental sessions to get a sufficient signal-to-noise ratio. Furthermore, we investigate the correlation of the EEG-based measures with the outcome of the standard behavioral assessment. Approach. As stimulus material, we used six gray-level natural images in six levels of degradation that were created by coding the images with the HM10.0 test model of the high efficiency video coding (H.265/MPEG-HEVC) using six different compression rates. The degraded images were presented in rapid alternation with the original images. In this setting, the presence of SSVEPs is a neural marker that objectively indicates the neural processing of the quality changes that are induced by the video coding. We tested two different machine learning methods to classify such potentials based on the modulation of the brain rhythm and on time-locked components, respectively. Main results. Results show high accuracies in classification of the neural signal over the threshold of the perception of the quality changes. Accuracies significantly correlate with the mean opinion scores given by the participants in the standardized degradation category rating quality assessment of the same group of images. Significance. The results show that neural assessment of video quality based on SSVEPs is a viable complement of the behavioral one and a significantly fast alternative to methods based on the P3 component.