Visual P300 Brain-Computer Interface Research Articles

Impact of Speller Size on a Visual P300 Brain-Computer Interface (BCI) System under Two Conditions of Constraint for Eye Movement.

The vast majority of P300-based brain-computer interface (BCI) systems are based on the well-known P300 speller presented by Farwell and Donchin for communication purposes and an alternative to people with neuromuscular disabilities, such as impaired eye movement. The purpose of the present work is to study the effect of speller size on P300-based BCI usability, measured in terms of effectiveness, efficiency, and satisfaction under overt and covert attention conditions. To this end, twelve participants used three speller sizes under both attentional conditions to spell 12 symbols. The results indicated that the speller size had, in both attentional conditions, a significant influence on performance. In both conditions (covert and overt), the best performances were obtained with the small and medium speller sizes, both being the most effective. The speller size did not significantly affect workload on the three speller sizes. In contrast, covert attention condition produced very high workload due to the increased resources expended to complete the task. Regarding users' preferences, significant differences were obtained between speller sizes. The small speller size was considered as the most complex, the most stressful, the less comfortable, and the most tiring. The medium speller size was always considered in the medium rank, which is the speller size that was evaluated less frequently and, for each dimension, the worst one. In this sense, the medium and the large speller sizes were considered as the most satisfactory. Finally, the medium speller size was the one to which the three standard dimensions were collected: high effectiveness, high efficiency, and high satisfaction. This work demonstrates that the speller size is an important parameter to consider in improving the usability of P300 BCI for communication purposes. The obtained results showed that using the proposed medium speller size, performance and satisfaction could be improved.

A Dynamic User Interface Based BCI Environmental Control System

ABSTRACTIn this study, a dynamic user interface (UI) is proposed in visual P300 Brain-Computer Interface (BCI) based environmental control system. A head-mounted Augmented Reality (AR) glass is used as the interactive media, which is used to assists the BCI system to build the dynamic UI with the scene in subject’s field of view. In the dynamic UI, based on the objects detected by the AR glass, options are dynamically generated. The subject can assign tasks by selecting different options in the dynamic UI. Five subjects successfully completed the task of controlling household appliances and navigating wheelchairs to designated destinations. Compared to static UI, the proposed dynamic UI has a 17.4% improvement in time delay. On average, only 1.9% of the commands resulted in incorrect operations. The dynamic UI makes progress in reducing time delay and incorrect operations. The proposed system provides a brand-new interactive method in BCI based applications.

Comparison of Four Control Methods for a Five-Choice Assistive Technology.

Severe motor impairments can affect the ability to communicate. The ability to see has a decisive influence on the augmentative and alternative communication (AAC) systems available to the user. To better understand the initial impressions users have of AAC systems we asked naïve healthy participants to compare two visual (a visual P300 brain-computer interface (BCI) and an eye-tracker) and two non-visual systems (an auditory and a tactile P300 BCI). Eleven healthy participants performed 20 selections in a five choice task with each system. The visual P300 BCI used face stimuli, the auditory P300 BCI used Japanese Hiragana syllables and the tactile P300 BCI used a stimulator on the small left finger, middle left finger, right thumb, middle right finger and small right finger. The eye-tracker required a dwell time of 3 s on the target for selection. We calculated accuracies and information-transfer rates (ITRs) for each control method using the selection time that yielded the highest ITR and an accuracy above 70% for each system. Accuracies of 88% were achieved with the visual P300 BCI (4.8 s selection time, 20.9 bits/min), of 70% with the auditory BCI (19.9 s, 3.3 bits/min), of 71% with the tactile BCI (18 s, 3.4 bits/min) and of 100% with the eye-tracker (5.1 s, 28.2 bits/min). Performance between eye-tracker and visual BCI correlated strongly, correlation between tactile and auditory BCI performance was lower. Our data showed no advantage for either non-visual system in terms of ITR but a lower correlation of performance which suggests that choosing the system which suits a particular user is of higher importance for non-visual systems than visual systems.

ERP variation may be negatively correlated with P300 speller performance

ERP variation may be negatively correlated with P300 speller performance

Long-Term Independent Brain-Computer Interface Home Use Improves Quality of Life of a Patient in the Locked-In State: A Case Study

ObjectiveDespite intense brain-computer interface (BCI) research for >2 decades, BCIs have hardly been established at patients' homes. The current study aimed at demonstrating expert independent BCI home use by a patient in the locked-in state and the effect it has on quality of life. DesignIn this case study, the P300 BCI-controlled application Brain Painting was facilitated and installed at the patient's home. Family and caregivers were trained in setting up the BCI system. After every BCI session, the end user indicated subjective level of control, loss of control, level of exhaustion, satisfaction, frustration, and enjoyment. To monitor BCI home use, evaluation data of every session were automatically sent and stored on a remote server. Satisfaction with the BCI as an assistive device and subjective workload was indicated by the patient. In accordance with the user-centered design, usability of the BCI was evaluated in terms of its effectiveness, efficiency, and satisfaction. The influence of the BCI on quality of life of the end user was assessed. SettingAt the patient's home. ParticipantA 73-year-old patient with amyotrophic lateral sclerosis in the locked-in state. InterventionsNot applicable. Main Outcome MeasureThe BCI has been used by the patient independent of experts for >14 months. The patient painted in about 200 BCI sessions (1–3 times per week) with a mean painting duration of 81.86 minutes (SD=52.15, maximum: 230.41). BCI improved quality of life of the patient. ResultsIn most of the BCI sessions the end user's satisfaction was high (mean=7.4, SD=3.24; range, 0–10). Dissatisfaction occurred mostly because of technical problems at the beginning of the study or varying BCI control. The subjective workload was moderate (mean=40.61; range, 0–100). The end user was highy satisfied with all components of the BCI (mean 4.42–5.0; range, 1–5). A perfect match between the user and the BCI technology was achieved (mean: 4.8; range, 1–5). Brain Painting had a positive impact on the patient's life on all three dimensions: competence (1.5), adaptability (2.17) and self-esteem (1.5); (range: –3 = maximum negative impact; 3 maximum positive impact). The patient had her first public art exhibition in July 2013; future exhibitions are in preparation. ConclusionsIndependent BCI home use is possible with high satisfaction for the end user. The BCI indeed positively influenced quality of life of the patient and supports social inclusion. Results demonstrate that visual P300 BCIs can be valuable for patients in the locked-in state even if other means of communication are still available (eye tracker).

Coherent Activity in Bilateral Parieto-Occipital Cortices during P300-BCI Operation.

The visual P300 brain–computer interface (BCI), a popular system for electroencephalography (EEG)-based BCI, uses the P300 event-related potential to select an icon arranged in a flicker matrix. In earlier studies, we used green/blue (GB) luminance and chromatic changes in the P300-BCI system and reported that this luminance and chromatic flicker matrix was associated with better performance and greater subject comfort compared with the conventional white/gray (WG) luminance flicker matrix. To highlight areas involved in improved P300-BCI performance, we used simultaneous EEG–fMRI recordings and showed enhanced activities in bilateral and right lateralized parieto-occipital areas. Here, to capture coherent activities of the areas during P300-BCI, we collected whole-head 306-channel magnetoencephalography data. When comparing functional connectivity between the right and left parieto-occipital channels, significantly greater functional connectivity in the alpha band was observed under the GB flicker matrix condition than under the WG flicker matrix condition. Current sources were estimated with a narrow-band adaptive spatial filter, and mean imaginary coherence was computed in the alpha band. Significantly greater coherence was observed in the right posterior parietal cortex under the GB than under the WG condition. Re-analysis of previous EEG-based P300-BCI data showed significant correlations between the power of the coherence of the bilateral parieto-occipital cortices and their performance accuracy. These results suggest that coherent activity in the bilateral parieto-occipital cortices plays a significant role in effectively driving the P300-BCI.

A region-based two-step P300-based brain–computer interface for patients with amyotrophic lateral sclerosis

ObjectiveThe P300-based brain–computer interface (BCI) is designed to help patients with motor disabilities to control their environment, and it has been used successfully in patients with amyotrophic lateral sclerosis (ALS). However, some ALS patients were unable to use the visual P300-BCI with the conventional row/column presentation. In this study, we evaluated the effect of a newly developed region-based two-step P300 speller, which has a larger flashing area than the conventional visual array. MethodsSeven ALS patients and seven age- and sex-matched able-bodied control subjects were required to input hiragana characters using our P300 BCI system. We prepared two types of input procedures, the conventional row/column (RC) speller and the two-step speller, and evaluated their online performance. ResultsThe mean online accuracy of the ALS patients was 24% for the RC condition and 55% for the two-step condition. The accuracy of the control subjects was 71% and 83% for the RC and two-step condition, respectively. Accuracy in ALS patients was significantly lower than that in the control subjects, and the new visual stimuli significantly increased accuracy of ALS patients. Using the new speller, two ALS patients showed an initial accuracy sufficient for practical use (>70%). The other two ALS patients, who performed better in the first trial using the new speller, continued to experience the BCI system, and their mean accuracy increased to 92%. ConclusionsThe two-step procedure for the visual P300 BCI system provided significantly increased accuracy for ALS patients compared with a conventional RC speller. SignificanceThe new region-based two-step P300 speller was effective in ALS patients, and the system may be beneficial to expand their range of activities.

Impact of Spatial Filters During Sensor Selection in a Visual P300 Brain-Computer Interface

A challenge in designing a Brain-Computer Interface (BCI) is the choice of the channels, e.g. the most relevant sensors. Although a setup with many sensors can be more efficient for the detection of Event-Related Potential (ERP) like the P300, it is relevant to consider only a low number of sensors for a commercial or clinical BCI application. Indeed, a reduced number of sensors can naturally increase the user comfort by reducing the time required for the installation of the EEG (electroencephalogram) cap and can decrease the price of the device. In this study, the influence of spatial filtering during the process of sensor selection is addressed. Two of them maximize the Signal to Signal-plus-Noise Ratio (SSNR) for the different sensor subsets while the third one maximizes the differences between the averaged P300 waveform and the non P300 waveform. We show that the locations of the most relevant sensors subsets for the detection of the P300 are highly dependent on the use of spatial filtering. Applied on data from 20 healthy subjects, this study proves that subsets obtained where sensors are suppressed in relation to their individual SSNR are less efficient than when sensors are suppressed in relation to their contribution once the different selected sensors are combined for enhancing the signal. In other words, it highlights the difference between estimating the P300 projection on the scalp and evaluating the more efficient sensor subsets for a P300-BCI. Finally, this study explores the issue of channel commonality across subjects. The results support the conclusion that spatial filters during the sensor selection procedure allow selecting better sensors for a visual P300 Brain-Computer Interface.

A tactile P300 brain-computer interface

In this study, we investigated a Brain-Computer Interface (BCI) based on EEG responses to vibro-tactile stimuli around the waist. P300 BCIs based on tactile stimuli have the advantage of not taxing the visual or auditory system and of being potentially unnoticeable to other people. A tactile BCI could be especially suitable for patients whose vision or eye movements are impaired. In Experiment 1, we investigated its feasibility and the effect of the number of equally spaced tactors. Whereas a large number of tactors is expected to enhance the P300 amplitude since the target will be less frequent, it could also negatively affect the P300 since it will be difficult to identify the target when tactor density increases. Participants were asked to attend to the vibrations of a target tactor, embedded within a stream of distracters. The number of tactors was two, four or six. We demonstrated the feasibility of a tactile P300 BCI. We did not find a difference in SWLDA classification performance between the different numbers of tactors. In a second set of experiments we reduced the stimulus onset asynchrony (SOA) by shortening the on- and/or off-time of the tactors. The SOA for an optimum performance as measured in our experiments turned out to be close to conventional SOAs of visual P300 BCIs.