Leandro da Silva-Sauer

Audio-cued motor imagery-based brain-computer interface: Navigation through virtual and real environments

The aim of this work is to provide a navigation paradigm that could be used to control a wheelchair through a brain-computer interface (BCI). In such a case, it is desirable to control the system without a graphical interface so that it will be useful for people without gaze control. Thus, an audio-cued paradigm with several navigation commands is proposed. In order to reduce the probability of misclassification, the BCI operates with only two mental tasks: relaxed state versus imagination of right hand movements; the use of motor imagery for navigation control is not yet extended among the auditory BCIs. Two experiments are described: in the first one, users practice the switch from a graphical to an audio-cued interface with a virtual wheelchair; in the second one, they change from virtual to real environments. The obtained results support the use of the proposed interface to control a real wheelchair without the need of a screen to provide visual stimuli or feedback.

Concentration on performance with P300-based BCI systems: a matter of interface features.

People who suffer from severe motor disabilities have difficulties to communicate with others or to interact with their environment using natural, i.e., muscular channels. These limitations can be overcome to some extent by using brain-computer interfaces (BCIs), because such systems allow users to communicate on the basis of their brain activity only. Among the several types of BCIs for spelling purposes, those that rely on the P300 event related potential-P300-based spellers-are chosen preferentially due to their high reliability. However, they demand from the user to sustain his/her attention to the desired character over a relatively long period of time. Therefore, the users capacity to concentrate can affect his/her performance with a P300-based speller. The aim of this study was to test this hypothesis using three different interfaces: one based on the classic P300 speller paradigm, another also based on that speller but including a word predictor, and a third one that was based on the T9 interface developed for mobile phones. User performance was assessed by measuring the time to complete a spelling task and the accuracy of character selection. The d2 test was applied to assess attention and concentration. Sample (Nxa0=xa014) was divided into two groups basing on of concentration scores. As a result, performance was better with the predictor-enriched interfaces: less time was needed to solve the task and participants made fewer errors (pxa0<xa0.05). There were also significant effects of concentration (pxa0<xa0.05) on performance with the standard P300 speller. In conclusion, the performance of those users with lower concentration level can be improved by providing BCIs with more interactive interfaces. These findings provide substantial evidence in order to highlight the impact of psychological features on BCI performance and should be taken into account for future assistive technology systems.

Audio-cued SMR brain-computer interface to drive a virtual wheelchair

In this work, an electroencephalographic analysis-based, self-paced (asynchronous) brain-computer interface (BCI) is proposed to control a virtual wheelchair using three different navigation commands: turn right, turn left and move forward. In order to reduce the probability of misclassification, the BCI is to be controlled with only two mental tasks (relaxed state versus imagination of right hand movements) using an audio-cued interface. Six healthy subjects participated in the experiment. After two training sessions controlling a wheelchair in a virtual environment using both a visual and auditory interface, all subjects successfully controlled the wheelchair in the last session, where the interface was only auditory. The obtained results support the use of the proposed interface to control a real wheelchair without the need of a screen to provide visual stimuli or feedback.

A two-class self-paced BCI to control a robot in four directions

In this work, an electroencephalographic analysis-based, self-paced (asynchronous) brain-computer interface (BCI) is proposed to control a mobile robot using four different navigation commands: turn right, turn left, move forward and move back. In order to reduce the probability of misclassification, the BCI is to be controlled with only two mental tasks (relaxed state versus imagination of right hand movements), using an audio-cued interface. Four healthy subjects participated in the experiment. After two sessions controlling a simulated robot in a virtual environment (which allowed the user to become familiar with the interface), three subjects successfully moved the robot in a real environment. The obtained results show that the proposed interface enables control over the robot, even for subjects with low BCI performance.

Brain-Computer Interface: Comparison of two paradigms to freely navigate in a virtual environment through one mental task

A Brain-Computer Interface (BCI) is a system that enables communication and control that is not based on muscular movements, but on brain activity. Some of these systems are based on discrimination of different mental tasks; usually they match the number of mental tasks to the number of control commands. In this paper, we will present a BCI system focused on the control of a virtual wheelchair. Our aim is to test different navigation paradigms to train subjects in a safe environment, prior to using it under real conditions. Due to the danger associated to a misclassification of the users intention in a navigation system, the BCI system was developed using the optimum number of mental states regarding the classification accuracy, that is, only two. However, the system let the subjects choose among several navigation commands using only one active mental task (versus any other mental activity). Mapping one task into a higher number of commands was carried out with two different paradigms: i) the first one let the subjects move in a continuous way while they kept this task active, and ii) the subjects used the mental task to switch their state on /off: they stopped if they were moving (advances and turns) and vice versa. Sixteen healthy and untrained subjects, divided into two groups, participated in an experiment in which each group used one of the paradigms. Preliminary results show that both paradigms can be used to navigate through virtual environments, although with the first one the times needed to complete a path were notably lower.

Training in Realistic Virtual Environments: Impact on User Performance in a Motor Imagery-Based Brain–Computer Interface

A brain–computer interface (BCI) is a system that enables people to control an external device by means of their brain activity, without the need of performing muscular activity. BCI systems are normally first tested on a controlled environment before being used in a real, daily scenario. While this is due to security reasons, the conditions that BCI systems users will eventually face in their usual environment may affect their performance in an unforeseen way. In this paper, we try to bridge this gap by presenting a trained BCI user a virtual environment that includes realistic distracting stimuli and testing whether the complexity or the type of such stimuli affects user performance. 11 subjects navigated two virtual environments: a static park and the same one with visual and auditory stimuli simulating typical distractors from a real park. No significant differences were found when using a realistic environment; in other words, the presence of different distracting stimuli did not worsen user performance.

A Shaping Procedure to Modulate Two Cognitive Tasks to Improve a Sensorimotor Rhythm-Based Brain-Computer Interface System

This study aimed to propose an adapted feedback using a psychological learning technique based on Skinners shaping method to help the users to modulate two cognitive tasks (right-hand motor imagination and relaxed state) and improve better control in a Brain-Computer Interface. In the first experiment, a comparative study between performance in standard feedback (N = 9) and shaping method (N = 10) was conducted. The NASA Task Load Index questionnaire was applied to measure the users workload. In the second experiment, a single case study was performed (N = 5) to verify the continuous learning by the shaping method. The first experiment showed significant interaction effect between sessions and group (F(1, 17) = 5.565; p = .031) which the shaping paradigm was applied. A second interaction effect demonstrates a higher performance increase in the relax state task with shaping procedure (F(1, 17) = 5. 038; p = .038). In NASA-TXL an interaction effect was obtained between the group and the cognitive task in Mental Demand (F(1, 17) = 6, 809; p = .018), Performance (F(1, 17) = 5, 725; p = .029), and Frustration (F(1, 17) = 9, 735; p = .006), no significance was found in Effort. In the second experiment, a trial-by-trial analysis shows an ascendant trend learning curve for the cognitive task with the lowest initial acquisition (relax state). The results suggest the effectiveness of the shaping procedure to modulate brain rhythms, improving mainly the cognitive task with greater initial difficulty and provide better interaction perception.