P300 BCI Research Articles

Источники и значимость вариативности потенциалов мозга человека в интерфейсе мозг–компьютер

In the brain-computer interface based on the P300 wave (P300 BCI), the selection of the command by the user becomes possible due to focusing the user's attention on the external stimulus/command and extraction of the response to this stimulus in the form of the event-related potential (ERP) components from EEG. To obtain the ERP signal, stimuli should be repeated many times, however, in view of the existing variability in latency of the response to certain stimuli, the averaged ERPs may give a distorted view of the nature of such responses and reduce accuracy of the interface. The study was aimed to develop an effective method for identification of the effects of the ERP components' latency variability and for accounting these effects in the P300 BCI, as well as to identify the possible impact of psychophysiological factors on the nature of ERP variability. We have conducted a BCI-based study of 19 healthy subjects involving extraction and adjustment of latency in the N1 and P300 spatial components, which play a key role in the command classification in the P300 BCI, to explore the mechanisms underlying variability. Such an approach ensured higher accuracy compared to the use of conventional EEG leads, and the highest increase of 10% was observed when using the minimum number of the stimulus repetitions. Furthermore, modifications of the interface allowing one to ensure a higher level of the user's focus on the task and a more accurate visual fixation on the target objects contributed to the increase in the amplitude of the ERP components by reducing variability of the responses to single stimuli. The findings emphasize the important role of the processes underlying the ERP components' variability and provide an effective tool for scientific exploration of such processes and the development of advanced BCI systems.

How Visual Stimuli Evoked P300 is Transforming the Brain-Computer Interface Landscape: A PRISMA Compliant Systematic Review.

Non-invasive Visual Stimuli evoked-EEG-based P300 BCIs have gained immense attention in recent years due to their ability to help patients with disability using BCI-controlled assistive devices and applications. In addition to the medical field, P300 BCI has applications in entertainment, robotics, and education. The current article systematically reviews 147 articles that were published between 2006-2021*. Articles that pass the pre-defined criteria are included in the study. Further, classification based on their primary focus, including article orientation, participants' age groups, tasks given, databases, the EEG devices used in the studies, classification models, and application domain, is performed. The application-based classification considers a vast horizon, including medical assessment, assistance, diagnosis, applications, robotics, entertainment, etc. The analysis highlights an increasing potential for P300 detection using visual stimuli as a prominent and legitimate research area and demonstrates a significant growth in the research interest in the field of BCI spellers utilizing P300. This expansion was largely driven by the spread of wireless EEG devices, advances in computational intelligence methods, machine learning, neural networks and deep learning.

Изучение эффектов вариативности потенциалов мозга человека в интерфейсе мозг–компьютер на волне P300

The P300-based brain–computer interfaces (P300 BCI) allow the user to select commands by focusing on them. The technology involves electroencephalographic (EEG) representation of the event-related potentials (ERP) that arise in response to repetitive external stimulation. Conventional procedures for ERP extraction and analysis imply that identical stimuli produce identical responses. However, the floating onset of EEG reactions is a known neurophysiological phenomenon. A failure to account for this source of variability may considerably skew the output and undermine the overall accuracy of the interface. This study aimed to analyze the effects of ERP variability in EEG reactions in order to minimize their influence on P300 BCI command classification accuracy. Healthy subjects aged 21–22 years (n = 12) were presented with a modified P300 BCI matrix moving with specified parameters within the working area. The results strongly support the inherent significance of ERP variability in P300 BCI environments. The correction of peak latencies in single EEG reactions provided a 1.5–2 fold increase in ERP amplitude with a concomitant enhancement of classification accuracy (from 71–78% to 92–95%, p < 0.0005). These effects were particularly pronounced in attention-demanding tasks with the highest matrix velocities. The findings underscore the importance of accounting for ERP variability in advanced BCI systems.

A study of classification techniques on P300 speller dataset

Communication is the basic need of humans to interact with their surroundings. BCI acts as a great tool for providing the means of basic communication to people with locked-in syndrome. For such patients, these basic things matter most and give them a sense of independence. Communication through BCI can be done using various paradigms, P300 speller is one of these paradigms in which the user is instructed to focus their attention on the desired character and able to produce negative and positive slow cortical potential changes which is then interpreted by the BCI system. Although P300 based BCI was introduced over twenty years ago, the past few years have seen a rapid increase in P300 based BCI research. In this paper, we overview the current status of P300 BCI technology and also discussed and compare different approaches using Random Forest, Support Vector Machine (SVM), and Extreme Gradient Boosting (XgBoost) classification algorithm.

Efficient Quadcopter Flight Control Using Hybrid SSVEP + P300 Visual Brain Computer Interface

ABSTRACT The objective of this study was to assess the feasibility of hybrid SSVEP + P300 visual BCI systems for quad-copter flight control in physical world. Existing BCI-based quad-copter flight control has limitations of slow navigation, lower system accuracy, rigorous user training requirement and lesser number of independent control commands. So, there is need of hybrid BCI design that combines evoked SSVEP and P300 potentials to control flight direction of quad-copter movement. GUI design is developed such that user can effectively control quad-copter flight by gazing at visual stimuli buttons that produce SSVEP & P300 potentials simultaneously in human cortex. We compare the performance metrics of the proposed flight control systems with other existing BCI-based flight control as conventional SSVEP BCI and P300 BCI and commercially available keyboard flight control systems. Results proved that the proposed system outperforms the existing BCI-based flight control systems but has slightly lower performance efficiency than the commercial keyboard flight control systems. Further, the proposed quad-copter flight control system proved its suitability for patients with severe motor disabilities.

2 Stages-region-based P300 Speller in Brain–Computer Interface

ABSTRACTBrain–computer interface (BCI) applications present communication model without using peripheral nerves and neuromuscular systems. The P300 waves are used in BCI applications. Signal classification accuracy is a significant parameter for P300 BCI application. In this study, our goal is to investigate P300 speller structure for higher classification accuracy. There are a lot studies about P300 speller variations of stimulus model. This models mostly includes about row–column-based visual or audio stimuli model P300 spellers. But there is not enough study about region-based P300 spellers. This study contributes to region-based P300 spellers researches. Our new paradigm 2-stages region-based P300 speller has different amount of regions and stimulus position. During the experiment also, row–column-based P300 speller was used for comparing accuracy rates with our unique design 2-stages region-based P300 speller. The subject focused on the desired character stimulus. We used the stepwise linear discriminant analysis (SWLDA) method for classification that either included the desired P300 signal or not. According to SWLDA, the maximum mean classification accuracy value of the experiment was 83.33% with 2-stages region-based P300 speller. With this new paradigm, the classification accuracy was improved by 23.89% according to the most commonly used row–column-based P300 speller.

Adapting the p300 brain-computer interface technology to assess condition of anorexia nervosa patients

Brain-computer interface based on the P300 wave (P300 BCI) allows activating a given command according to the electroencephalogram (EEG) response to a predetermined relevant stimulus. The same algorithm enables detecting a subjectively important item (i.e., one triggering emotional response) in an environment even without actively drawing attention to it. Such systems allow assessing the personal significance of certain information, which can be used in the diagnostics of disorders of emotional perception or value system, e.g., eating disorders. This study aimed to investigate the EEG responses of anorexia nervosa patients (diagnosis F50.0, n = 12, age 11–16 years) to the stimuli with different perceived emotional significance, as well as to validate application of P300 BCI to detect the focus of attention to subjectively important stimuli. The inclusion criteria were: diagnosed anorexia nervosa (diagnosis F50.0); active rehabilitation. We registered the EEG while presenting images with different content to the patients. The event-related potentials (ERP) were detected and analyzed with the help of MATLAB 7.1 (MathWorks; USA). Statistica 7.0 software (StatSoft; USA) was used for statistical analysis of the data. We have discovered that in passive viewing paradigm, images of body parts of emaciated people among other images caused ERP with higher amplitude than images of food. Moreover, the accuracy of detection was higher for images of body parts: 89% against 59%, respectively. Thus, we have proven the validity of applying P300 BCI to detect covert emotional foci of attention and added to the existing knowledge about the mechanisms of development of anorexia nervosa.

Selection of effective probes for an individual to identify P300 signal generated from P300 BCI speller

Selection of effective probes for an individual to identify P300 signal generated from P300 BCI speller

Selection of effective probes for an individual to identify P300 signal generated from P300 BCI speller

P300 is a strong event related potential (ERP) generated in the brain and observed on the scalp when an unusual event happens. To decipher P300 signal, we have to use the property of P300 to distinguish P300 signal from non-P300 signal. In this work, we used data collected from P300 BCI Speller with 128 probes. Conventional BCI speller uses eight probes at pre-defined locations on the skull. Though P300 is strong in the parietal region of the brain, location of the strongest signal varies from person to person. The idea is that, if we optimise probe locations for an individual, we could reduce the number of probes required. In fact, the process mode for the raw brain wave signals also will affect the classification accuracy. We designed an algorithm to analyse the raw signals. We achieved over 81% classification accuracy on average with only three probes from only one target stimulus and one non-target stimulus.

Objective eye movements during typing in P300 BCI: the effect of stimuli size and spacing

Objective eye movements during typing in P300 BCI: the effect of stimuli size and spacing

Usage of drip drops as stimuli in an auditory P300 BCI paradigm.

Recently, many auditory BCIs are using beeps as auditory stimuli, while beeps sound unnatural and unpleasant for some people. It is proved that natural sounds make people feel comfortable, decrease fatigue, and improve the performance of auditory BCI systems. Drip drop is a kind of natural sounds that makes humans feel relaxed and comfortable. In this work, three kinds of drip drops were used as stimuli in an auditory-based BCI system to improve the user-friendness of the system. This study explored whether drip drops could be used as stimuli in the auditory BCI system. The auditory BCI paradigm with drip-drop stimuli, which was called the drip-drop paradigm (DP), was compared with the auditory paradigm with beep stimuli, also known as the beep paradigm (BP), in items of event-related potential amplitudes, online accuracies and scores on the likability and difficulty to demonstrate the advantages of DP. DP obtained significantly higher online accuracy and information transfer rate than the BP (p<0.05, Wilcoxon signed test; p<0.05, Wilcoxon signed test). Besides, DP obtained higher scores on the likability with no significant difference on the difficulty (p<0.05, Wilcoxon signed test). The results showed that the drip drops were reliable acoustic materials as stimuli in an auditory BCI system.

Параметры окуломоторной активности оператора в интерфейсе «мозг–компьютер» на волне P300 и в аналогичных стимульных ситуациях

&lt;p&gt;Hypotheses about the relationship of the processes of visual perception and variations of the task in an identical stimulus environment was tested. The following tasks were tested: 1) a simple observation of the illuminations of the character in the matrix; 2) counting the number of highlights; 3) monitoring of the target symbol highlights and typing text with the P300 BCI. In a group of 14 people showed that the highest average length of visual fixation and the lowest dispersion of fixation observed for the second type of task. Statistically significant differences in the level of dispersion of visual fixations found between 1-2 and 1-3 modes; differences between the modes for the duration of fixations are at trends. Significant differences in the number of visual fixations on the target symbols wasn&amp;rsquo;t detected. The overall conclusion is the high perspective of pairing methodology brain-computer interface on the P300 wave with eye tracking to optimize the characteristics of the stimulus in the BCI environment. The differences in the parameters of oculomotor activity between the tasks reflect the level of attention concentration in the target symbols of the P300 BCI&lt;/p&gt;

Design of an auditory P300 BCI speller for the Japanese Hiragana syllabary

Design of an auditory P300 BCI speller for the Japanese Hiragana syllabary

A survey of the dummy face and human face stimuli used in BCI paradigm.

It was proved that the human face stimulus were superior to the flash only stimulus in BCI system. However, human face stimulus may lead to copyright infringement problems and was hard to be edited according to the requirement of the BCI study. Recently, it was reported that facial expression changes could be done by changing a curve in a dummy face which could obtain good performance when it was applied to visual-based P300 BCI systems. In this paper, four different paradigms were presented, which were called dummy face pattern, human face pattern, inverted dummy face pattern and inverted human face pattern, to evaluate the performance of the dummy faces stimuli compared with the human faces stimuli. The key point that determined the value of dummy faces in BCI systems were whether dummy faces stimuli could obtain as good performance as human faces stimuli. Online and offline results of four different paradigms would have been obtained and comparatively analyzed. Online and offline results showed that there was no significant difference among dummy faces and human faces in ERPs, classification accuracy and information transfer rate when they were applied in BCI systems. Dummy faces stimuli could evoke large ERPs and obtain as high classification accuracy and information transfer rate as the human faces stimuli. Since dummy faces were easy to be edited and had no copyright infringement problems, it would be a good choice for optimizing the stimuli of BCI systems.

The Component Structure of Event-Related Potentials in the P300 Speller Paradigm

We investigated the componential structure of event-related potentials elicited while participants use the P300 BCI. Six healthy participants "typed" all characters in a 6 × 6 matrix twice in a random sequence. A principal component analysis indicated that in addition to the P300, target flashes elicited an earlier frontal positivity, possibly a Novelty P3. The amplitudes of both P300 and the Novelty P3 varied with the matrix row in which the target character was located. However, the P300 elicited by row flashes was largest for targets in the lower part of the matrix, whereas the Novelty P3 elicited by column flashes was largest in the top part. Classification accuracy using stepwise linear discriminant analysis mirrored the pattern in the Novelty P3 (an accuracy difference of 0.1 between rows 1 and 6). When separate classifiers were generated to rely solely on the P300 or solely on the Novelty P3, the latter function led to higher accuracy (a mean accuracy difference of about 0.2 between classifiers). A possible explanation is that some nontarget flashes elicit a P300, leading to lower selection accuracy of the respective classifier. In an additional set of data from six different participants we replicated the ERP structure of the initial analyses and characterized the spatial distributions more closely by using a dense electrode array. Overall, our findings provide new insights in the componential structure of ERPs elicited in the P300 speller paradigm and have important implications for optimizing the speller's selection accuracy.

Adapting the P300-Based Brain–Computer Interface for Gaming: A Review

The P300-based brain-computer interface (P300 BCI) is currently a very popular topic in assistive technology development. However, only a few simple P300 BCI-based games have been designed so far. Here, we analyze the shortcomings of this BCI in gaming applications and show that solutions for overcoming them already exist, although these techniques are dispersed over several different games. Additionally, new approaches to improve the P300 BCI accuracy and flexibility are currently being proposed in the more general P300 BCI research. The P300 BCI, even in its current form, not only exhibits relatively high speed and accuracy, but also can be used without user training, after a short calibration. Taking these facts together, the broader use of the P300 BCI in BCI-controlled video games is recommended.

F078 Estimation of hearing loss in children: comparison of auditory steady-state response (ASSR), and behavioral test methods to improve fitting of Traditional Hearing Aids

An EEG-based brain–computer system can be used to control external devices such as computers, wheelchairs or Virtual Environments. One of the most important applications is a spelling device to aid severely disabled individuals with communication, for example people disabled by amyotrophic lateral sclerosis (ALS). P300-based BCI systems are optimal for spelling characters with high speed and accuracy, as compared to other BCI paradigms such as motor imagery. In this study, 100 subjects tested a P300-based BCI system to spell a 5-character word with only 5 min of training. EEG data were acquired while the subject looked at a 36-character matrix to spell the word WATER. Two different versions of the P300 speller were used: (i) the row/column speller (RC) that flashes an entire column or row of characters and (ii) a single character speller (SC) that flashes each character individually. The subjects were free to decide which version to test. Nineteen subjects opted to test both versions. The BCI system classifier was trained on the data collected for the word WATER. During the real-time phase of the experiment, the subject spelled the word LUCAS, and was provided with the classifier selection accuracy after each of the five letters. Additionally, subjects filled out a questionnaire about age, sex, education, sleep duration, working duration, cigarette consumption, coffee consumption, and level of disturbance that the flashing characters produced. 72.8% (N = 81) of the subjects were able to spell with 100% accuracy in the RC paradigm and 55.3% (N = 38) of the subjects spelled with 100% accuracy in the SC paradigm. Less than 3% of the subjects did not spell any character correctly. People who slept less than 8 h performed significantly better than other subjects. Sex, education, working duration, and cigarette and coffee consumption were not statistically related to differences in accuracy. The disturbance of the flashing characters was rated with a median score of 1 on a scale from 1 to 5 (1, not disturbing; 5, highly disturbing). This study shows that high spelling accuracy can be achieved with the P300 BCI system using approximately 5 min of training data for a large number of non-disabled subjects, and that the RC paradigm is superior to the SC paradigm. 89% of the 81 RC subjects were able to spell with accuracy 80–100%. A similar study using a motor imagery BCI with 99 subjects showed that only 19% of the subjects were able to achieve accuracy of 80–100%. These large differences in accuracy suggest that with limited amounts of training data the P300-based BCI is superior to the motor imagery BCI. Overall, these results are very encouraging and a similar study should be conducted with subjects who have ALS to determine if their accuracy levels are similar.

Green/blue flicker matrices for the P300 BCI improve the subjective feeling of comfort

Green/blue flicker matrices for the P300 BCI improve the subjective feeling of comfort