Effects of Feedback latency on P300-based Brain-computer Interface

Feedback has been shown to affect performance when using a Brain-Computer Interface (BCI) based on sensorimotor rhythms. In contrast, little is known about the influence of feedback on P300-based BCIs. There is still an open question whether feedback affects the regulation of P300 and consequently the operation of P300-based BCIs. In this paper, for the first time, the influence of feedback on the P300-based BCI speller task is systematically assessed. For this purpose, 24 healthy participants performed the classic P300-based BCI speller task, while only half of them received feedback. Importantly, the number of flashes per letter was reduced on a regular basis in order to increase the frequency of providing feedback. Experimental results showed that feedback could significantly improve the P300-based BCI speller performance, if it was provided in short time intervals (e.g. in sequences as short as 4 to 6 flashes per row/column). Moreover, our offline analysis showed that providing feedback remarkably enhanced the relevant ERP patterns and attenuated the irrelevant ERP patterns, such that the discrimination between target and non-target EEG trials increased

Online home appliance control using EEG-Based brain-computer interfaces

Brain???computer interfaces (BCIs) allow patients with paralysis to control external devices by mental commands. Recent advances in home automation and the Internet of things may extend the horizon of BCI applications into daily living environments at home. In this study, we developed an online BCI based on scalp electroencephalography (EEG) to control home appliances. The BCI users controlled TV channels, a digital door-lock system, and an electric light system in an unshielded environment. The BCI was designed to harness P300 andN200 components of event-related potentials (ERPs). On average, the BCI users could control TV channels with an accuracy of 83.0% ?? 17.9%, the digital door-lock with 78.7% ?? 16.2% accuracy, and the light with 80.0% ?? 15.6% accuracy, respectively. Our study demonstrates a feasibility to control multiple home appliances using EEG-based BCIs

Emotional Brain-Computer Interfaces

Research in Brain-computer interface (BCI) has significantly increased during the last few years. In addition to their initial role as assisting devices for the physically challenged, BCIs are now proposed for a wider range of applications. As in any HCI application, BCIs can also benefit from adapting their operation to the emotional state of the user. BCIs have the advantage of having access to brain activity which can provide signicant insight into the user's emotional state. This information can be utilized in two manners. 1) Knowledge of the inuence of the emotional state on brain activity patterns can allow the BCI to adapt its recognition algorithms, so that the intention of the user is still correctly interpreted in spite of signal deviations induced by the subject's emotional state. 2) The ability to recognize emotions can be used in BCIs to provide the user with more natural ways of controlling the BCI through affective modulation. Thus, controlling a BCI by recollecting a pleasant memory can be possible and can potentially lead to higher information transfer rates.\ud These two approaches of emotion utilization in BCI are elaborated in detail in this paper in the framework of noninvasive EEG based BCIs

Is the P300 Speller Independent?

The P300 speller is being considered as an independent brain-computer interface. That means it measures the user's intent, and does not require the user to move any muscles. In particular it should not require eye fixation of the desired character. However, it has been shown that posterior electrodes provide significant discriminative information, which is likely related to visual processing. These findings imply the need for studies controlling the effect of eye movements. In experiments with a 3x3 character matrix, attention and eye fixation was directed to different characters. In the event-related potentials, a P300 occurred for the attended character, and N200 was seen for the trials showing the focussed character. It occurred at posterior sites, reaching its peak at 200ms after stimulus onset. The results suggest that gaze direction plays an important role in P300 speller paradigm. By controlling gaze direction it is possible to separate voluntary and involuntary EEG responses to the highlighting of characters.Comment: 7 pages, 5 figure

Defining brain–machine interface applications by matching interface performance with device requirements

Interaction with machines is mediated by human-machine interfaces (HMIs). Brain-machine interfaces (BMIs) are a particular class of HMIs and have so far been studied as a communication means for people who have little or no voluntary control of muscle activity. In this context, low-performing interfaces can be considered as prosthetic applications. On the other hand, for able-bodied users, a BMI would only be practical if conceived as an augmenting interface. In this paper, a method is introduced for pointing out effective combinations of interfaces and devices for creating real-world applications. First, devices for domotics, rehabilitation and assistive robotics, and their requirements, in terms of throughput and latency, are described. Second, HMIs are classified and their performance described, still in terms of throughput and latency. Then device requirements are matched with performance of available interfaces. Simple rehabilitation and domotics devices can be easily controlled by means of BMI technology. Prosthetic hands and wheelchairs are suitable applications but do not attain optimal interactivity. Regarding humanoid robotics, the head and the trunk can be controlled by means of BMIs, while other parts require too much throughput. Robotic arms, which have been controlled by means of cortical invasive interfaces in animal studies, could be the next frontier for non-invasive BMIs. Combining smart controllers with BMIs could improve interactivity and boost BMI applications. © 2007 Elsevier B.V. All rights reserved

Effects of training and motivation on auditory P300 brain–computer interface performance

Objectives Brain–computer interface (BCI) technology aims at helping end-users with severe motor paralysis to communicate with their environment without using the natural output pathways of the brain. For end-users in complete paralysis, loss of gaze control may necessitate non-visual BCI systems. The present study investigated the effect of training on performance with an auditory P300 multi-class speller paradigm. For half of the participants, spatial cues were added to the auditory stimuli to see whether performance can be further optimized. The influence of motivation, mood and workload on performance and P300 component was also examined. Methods In five sessions, 16 healthy participants were instructed to spell several words by attending to animal sounds representing the rows and columns of a 5 × 5 letter matrix. Results 81% of the participants achieved an average online accuracy of ≥70%. From the first to the fifth session information transfer rates increased from 3.72 bits/min to 5.63 bits/min. Motivation significantly influenced P300 amplitude and online ITR. No significant facilitative effect of spatial cues on performance was observed. Conclusions Training improves performance in an auditory BCI paradigm. Motivation influences performance and P300 amplitude. Significance The described auditory BCI system may help end-users to communicate independently of gaze control with their environment

P300-Based BCI Performance Prediction through Examination of Paradigm Manipulations and Principal Components Analysis.

Severe neuromuscular disorders can produce locked-in syndrome (LIS), a loss of nearly all voluntary muscle control. A brain-computer interface (BCI) using the P300 event-related potential provides communication that does not depend on neuromuscular activity and can be useful for those with LIS. Currently, there is no way of determining the effectiveness of P300-based BCIs without testing a person\u27s performance multiple times. Additionally, P300 responses in BCI tasks may not resemble the typical P300 response. I sought to clarify the relationship between the P300 response and BCI task parameters and examine the possibility of a predictive relationship between traditional oddball tasks and BCI performance. Both waveform and component analysis have revealed several task-dependent aspects of brain activity that show significant correlation with the user\u27s performance. These components may provide a fast and reliable metric to indicate whether the BCI system will work for a given individual

A New Auditory Multi-Class Brain-Computer Interface Paradigm: Spatial Hearing as an Informative Cue

Most P300-based brain-computer interface (BCI) approaches use the visual modality for stimulation. For use with patients suffering from amyotrophic lateral sclerosis (ALS) this might not be the preferable choice because of sight deterioration. Moreover, using a modality different from the visual one minimizes interference with possible visual feedback. Therefore, a multi-class BCI paradigm is proposed that uses spatially distributed, auditory cues. Ten healthy subjects participated in an offline oddball task with the spatial location of the stimuli being a discriminating cue. Experiments were done in free field, with an individual speaker for each location. Different inter-stimulus intervals of 1000 ms, 300 ms and 175 ms were tested. With averaging over multiple repetitions, selection scores went over 90% for most conditions, i.e., in over 90% of the trials the correct location was selected. One subject reached a 100% correct score. Corresponding information transfer rates were high, up to an average score of 17.39 bits/minute for the 175 ms condition (best subject 25.20 bits/minute). When presenting the stimuli through a single speaker, thus effectively canceling the spatial properties of the cue, selection scores went down below 70% for most subjects. We conclude that the proposed spatial auditory paradigm is successful for healthy subjects and shows promising results that may lead to a fast BCI that solely relies on the auditory sense