Andreas Pinegger

Brain-controlled applications using dynamic P300 speller matrices

OBJECTIVES Access to the world wide web and multimedia content is an important aspect of life. We present a web browser and a multimedia user interface adapted for control with a brain-computer interface (BCI) which can be used by severely motor impaired persons. METHODS The web browser dynamically determines the most efficient P300 BCI matrix size to select the links on the current website. This enables control of the web browser with fewer commands and smaller matrices. The multimedia player was based on an existing software. Both applications were evaluated with a sample of ten healthy participants and three end-users. All participants used a visual P300 BCI with face-stimuli for control. RESULTS The healthy participants completed the multimedia player task with 90% accuracy and the web browsing task with 85% accuracy. The end-users completed the tasks with 62% and 58% accuracy. All healthy participants and two out of three end-users reported that they felt to be in control of the system. CONCLUSIONS In this study we presented a multimedia application and an efficient web browser implemented for control with a BCI. SIGNIFICANCE Both applications provide access to important areas of modern information retrieval and entertainment.

Control or non-control state: that is the question! An asynchronous visual P300-based BCI approach

OBJECTIVE Brain-computer interfaces (BCI) based on event-related potentials (ERP) were proven to be a reliable synchronous communication method. For everyday life situations, however, this synchronous mode is impractical because the system will deliver a selection even if the user is not paying attention to the stimulation. So far, research into attention-aware visual ERP-BCIs (i.e., asynchronous ERP-BCIs) has led to variable success. In this study, we investigate new approaches for detection of user engagement. APPROACH Classifier output and frequency-domain features of electroencephalogram signals as well as the hybridization of them were used to detect the users state. We tested their capabilities for state detection in different control scenarios on offline data from 21 healthy volunteers. MAIN RESULTS The hybridization of classifier output and frequency-domain features outperformed the results of the single methods, and allowed building an asynchronous P300-based BCI with an average correct state detection accuracy of more than 95%. SIGNIFICANCE Our results show that all introduced approaches for state detection in an asynchronous P300-based BCI can effectively avoid involuntary selections, and that the hybrid method is the most effective approach.

A P300 BCI for e - inclusion, cognitive rehabilitation and smart home control

We implemented an easy-to-use P300 BCI system that allows users to control a variety of applications for communication, creative expression, training of cognitive abilities and environmental control. In this paper we present an evaluation of the following four applications: a speller, two games that can be used for cognitive rehabilitation or entertainment, twitter (via web browser) and a webcam. All fourteen healthy participants had control over the BCI and reached high accuracies (>85%). The results of the evaluation informed the development of the next prototype. With a user-centered approach we aim to further improve the prototype and ultimately provide end users with a multifunctional system that can be used as assistive technology in a home environment.

Introduction of a Universal P300 Brain-Computer Interface Communication System.

We developed a new P300-based BCI communication system. The design is tripartite: One part operates as a universal data acquisition unit, which allows to easily use different data acquisition devices. The second part is a rapid prototyping platform based on Matlab/Simulink R

Evaluation of Different EEG Acquisition Systems Concerning Their Suitability for Building a Brain–Computer Interface: Case Studies

One important aspect in non-invasive brain–computer interface (BCI) research is to acquire the electroencephalogram (EEG) in a proper way. From an end-user perspective, it means with maximum comfort and without any extra inconveniences (e.g., washing the hair), whereas from a technical perspective, the signal quality has to be optimal to make the BCI work effectively and efficiently. In this work, we evaluated three different commercially available EEG acquisition systems that differ in the type of electrodes (gel-, water-, and dry-based), the amplifier technique, and the data transmission method. Every system was tested regarding three different aspects, namely, technical, BCI effectiveness and efficiency (P300 communication and control), and user satisfaction (comfort). We found that water-based system had the lowest short circuit noise level, the hydrogel-based system had the highest P300 spelling accuracies, and the dry electrode-based system caused the least inconveniences. Therefore, building a reliable BCI is possible with all the evaluated systems, and it is on the user to decide which system meets the given requirements best.

Write, read and answer emails with a dry ‘n’ wireless brain-computer interface system

Brain-computer interface (BCI) users can control very complex applications such as multimedia players or even web browsers. Therefore, different biosignal acquisition systems are available to noninvasively measure the electrical activity of the brain, the electroencephalogram (EEG). To make BCIs more practical, hardware and software are nowadays designed more user centered and user friendly. In this paper we evaluated one of the latest innovations in the area of BCI: A wireless EEG amplifier with dry electrode technology combined with a web browser which enables BCI users to use standard webmail. With this system ten volunteers performed a daily life task: Write, read and answer an email. Experimental results of this study demonstrate the power of the introduced BCI system.

Sheet music by mind: Towards a brain-computer interface for composing

Providing brain-computer interface (BCI) users engaging applications should be one of the main targets in BCI research. A painting application, a web browser and other applications can already be controlled via BCI. Another engaging application would be a music composer for self-expression. In this work, we describe Brain Composing: A BCI controlled music composing software. We tested and evaluated the implemented brain composing system with five volunteers. Using a tap water-based electrode biosignal amplifier further improved the usability of the system. Three participants reached accuracies above 77% and were able to copy-compose a given melody. Results of questionnaires support that our brain composing system is an attractive and easy way to compose music via a BCI.

Composing only by thought: Novel application of the P300 brain-computer interface

The P300 event-related potential is a well-known pattern in the electroencephalogram (EEG). This kind of brain signal is used for many different brain-computer interface (BCI) applications, e.g., spellers, environmental controllers, web browsers, or for painting. In recent times, BCI systems are mature enough to leave the laboratories to be used by the end-users, namely severely disabled people. Therefore, new challenges arise and the systems should be implemented and evaluated according to user-centered design (USD) guidelines. We developed and implemented a new system that utilizes the P300 pattern to compose music. Our Brain Composing system consists of three parts: the EEG acquisition device, the P300-based BCI, and the music composing software. Seventeen musical participants and one professional composer performed a copy-spelling, a copy-composing, and a free-composing task with the system. According to the USD guidelines, we investigated the efficiency, the effectiveness and subjective criteria in terms of satisfaction, enjoyment, frustration, and attractiveness. The musical participants group achieved high average accuracies: 88.24% (copy-spelling), 88.58% (copy-composing), and 76.51% (free-composing). The professional composer achieved also high accuracies: 100% (copy-spelling), 93.62% (copy-composing), and 98.20% (free-composing). General results regarding the subjective criteria evaluation were that the participants enjoyed the usage of the Brain Composing system and were highly satisfied with the system. Showing very positive results with healthy people in this study, this was the first step towards a music composing system for severely disabled people.

Towards non-invasive EEG-based arm/hand-control in users with spinal cord injury

Restoring the ability to reach and grasp can dramatically improve quality of life for people with cervical spinal cord injury (SCI). The main challenge in restoring independent reaching and grasping in patients is to develop assistive technologies with intuitive and non-invasive user interfaces. We believe that this challenge can be met by directly translating movement-related brain activity into control signals. During the last decade, we have conducted research on EEG-based brain-computer interfaces (BCIs) for the decoding of movement parameters, such as trajectories and targets. Although our findings are promising, the control is still unnatural. Therefore, we surmise that natural and intuitive control of neuroprostheses could be achieved by developing a novel control framework that incorporates detection of goal directed movement intention, movement decoding, identifying the type of grasp, error potentials detection and delivery of feedback.