Günter Edlinger

• g.tec

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together...

Functional near-infrared spectroscopy (fNIRS) applied to brain monitoring has been gaining increasing relevance in the last years due to its not invasive nature and the capability to work in combination with other well–known techniques such as the EEG. The possible use cases span from neural-rehabilitation to early diagnosis of some neural diseases...

Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor disablities, and thus assessing their spared cognitive abilities can be difficult. Recent research from several groups has shown that non-invasive brain-computer interface (BCI) technology can provide assessments of these patients' cognitive function that can supple...

Brain-computer interface (BCI) technology has recently been extended to help patients with disorders of consciousness (DOC) and stroke. These two promising new directions focus on new patient groups and new applications for these groups. First, patients diagnosed with a DOC might benefit from new BCI-based systems that can help assess (or reassess)...

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction technique...

Electrical cortical stimulation (ECS) is often used in presurgical evaluation procedures for patients suffering from pharmacoresistant epilepsy. Real-time functional mapping (RTFM) is an alternative brain mapping methodology that can accompany traditional functional mapping approaches like ECS. In this paper, we present a combined RTFM/ECS system t...

Conventional therapies do not provide paralyzed patients with closed-loop sensorimotor integration for motor rehabilitation. This work presents the recoveriX system, a hardware and software platform that combines a motor imagery (MI)-based brain-computer interface (BCI), functional electrical stimulation (FES), and visual feedback technologies for...

Brain-computer interface (BCI) technology is increasingly used to research new methods to provide assessment and communication for patients diagnosed with a disorder of consciousness (DOC). As this technology advances, it could lead to tools that could support clinical diagnoses, provide communication to some persons who cannot otherwise communicat...

Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, w...

Recent work has sought to extend brain-computer interface (BCI) technology to persons diagnosed with a disorder of consciousness (DOC). This new approach can use real-time measures of brain activity to facilitate assessment of conscious awareness, and potentially provide communication for some users. We present the mindBEAGLE system, a hardware and...

In conventional rehabilitation therapy to help persons with stroke recover movement, there is no objective way to evaluate each patient’s motor imagery. Thus, patients may receive rewarding feedback even when they are not complying with the task instructions to imagine specific movements. Paired associative stimulation (PAS) uses brain-computer int...

Conventional therapies do not provide paralyzed patients with closed-loop sensorimotor integration for motor rehabilitation. Paired associative stimulation (PAS) uses brain-computer interface (BCI) technology to monitor patients’ movement imagery in real-time, and utilizes the information to control functional electrical stimulation (FES) and bar f...

Conventional therapies do not provide paralyzed patients with closed-loop sensorimotor integration for motor rehabilitation. Paired associative stimulation (PAS) uses brain-computer interface (BCI) technology to monitor patients’ movement imagery in real-time, and utilizes the information to control functional electrical stimulation (FES) and bar f...

Although simultaneous measurement of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is one of the most valuable methods for studying human brain activity non-invasively, it remains challenging to measure high quality EEG inside the MRI scanner. Recently, a new approach for minimizing residual MRI scanner artifacts in...

In the last years, Brain Neural Computer Interfaces (BNCIs) have been investigated and several applications have been proposed. Those systems have been explored almost exclusively in laboratories with developers and researchers. Home usage has been demonstrated, though only with on-going expert supervision. In this paper, we present a BNCI for ever...

This publication presents a novel device for BCI based stroke rehabilitation, using two feedback modalities: visually, via an avatar showing the desired movements in the user’s first perspective; and via electrical stimulation of the relevant muscles. Three different kinds of movements can be trained: wrist dorsiflexion, elbow flexion and knee exte...

Most brain–computer interface (BCI) systems utilize one of three approaches: sensorimotor rhythms (SMRs), P300s, or steady-state visually evoked potentials (SSVEPs). Numerous groups have reported that these approaches do not provide effective communication for a small percentage of users. This phenomenon has been called BCI illiteracy, inefficiency...

In a brain-computer interface (BCI), users perform specific mental tasks to convey messages or commands through direct measures of brain activity. Typically, users must perform each mental task for two or more seconds before their brain activity is distinct enough for accurate classification. In P300 BCIs, this usually entails silently counting spe...

Imagine being able to think, hear, and feel - but not move or communicate. Over 40% of patients diagnosed as vegetative are reclassified as (at least) minimally conscious when assessed by expert teams. This publication presents a device that uses BCI (Brain-Computer Interface) technology for quick and easy assessment of patients suffering a disorde...

Brain–computer interfaces have been improved dramatically over recent years and many new applications have been developed. This chapter describes some of the most important and interesting systems and concepts that are already available on the market or that will come to market soon: spelling, gaming, painting, avatar control, stroke rehabilitation...

This work introduces a new system to allow persons with motor disabilities to control remote devices and communicate with their environment. This system consists of a real-time data processing computer that analyzes biosignals like the electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG) and a second computer that controls a sma...

In this publication, we present a Motor Imagery (MI) based Brain-Computer Interface (BCI) for neurologic rehabilitation. The BCI is able to control two different feedback devices. The first one is a rehabilitation robot, moving the fingers of the affected hand according to the detected MI. The second one presents feedback via virtual reality (VR) t...

The electroencephalogram (EEG) provides a noninvasive way to record and analyze brain functions in real time. For brain—computer interfaces (BCIs), slow waves, evoked potentials, and activation in the alpha, beta, and gamma bands are used. When a real-time biosignal processing system is confi gured, several influencing components have to be conside...

This chapter provides a general introduction to brain–computer interfaces (BCIs). It outlines general principles of BCI systems and the need for general-purpose BCI software. It also gives an overview of the BCI2000 system and describes the target audience for BCI2000 generally and this book specifically.

Brain-computer interfaces (BCI) are communication systems that allow people to send messages or commands without movement. BCIs rely on different types of signals in the electroencephalogram (EEG), typically P300s, steady-state visually evoked potentials (SSVEP), or event-related desynchronization. Early BCI systems were often evaluated with a sele...

Brain-computer interface (BCI) systems translate brain activity into messages or commands. BCI studies that record from a dozen or more subjects typically report substantial variations in performance, as measured by accuracy. Usually, some subjects attain excellent (even perfect) accuracy, while at least one subject performs so poorly that effectiv...

A BCI enables a new communication channel that bypasses the standard neural pathways and output channels and in order to control an external device. BCI technology has been developed to enable lost body or communication functions in handicapped persons. Recently BCI systems are used for communication purposes, to control robotic devices to control...

A BCI enables a new communication channel that bypasses the standard neural pathways and output channels and in order to control an external device. Recently BCI systems are used for communication purposes, to control robotic devices to control games or for rehabilitation. A limiting factor in the wide-spread application is the usage of abrasive ge...

A Brain-computer interface (BCI) provides a new communication channel for a human without using any muscle activities. Within this study we propose hybrid BCI based on the P300 evoked potential and steady-state visually evoked potential (SSVEP) approach to control a smart home environment in an asynchronous way. Firstly a P300 based BCI system was...

Most brain–computer interfaces (BCIs) rely on one of three types of signals in the electroencephalogram (EEG): P300s, steady-state visually evoked potentials, and event-related desynchronization. EEG is typically recorded non-invasively with electrodes mounted on the human scalp using conductive electrode gel for optimal impedance and data quality....

For this study a P300 BCI speller application framework served as a base to explore the operation for three different applications. Subjects exchanged messages in the networks of (i) Twitter (Twitter Inc.) and socialized with other residents in Second Life (Linden Lab) and (ii) controlled a virtual smart home. Although the complexity of the variou...

Brain-computer interfaces (BCI) provide a new communication channel between the human brain and a computer without using any muscle activities. Applications of BCI systems comprise communication, restoration of movements or environmental control. Within this study we propose a combined P300 and steady-state visually evoked potential (SSVEP) based B...

Brain–computer interfaces (BCI) are using the electroencephalogram, the electrocorticogram and trains of action potentials as inputs to analyze brain activity for communication purposes and/or the control of external devices. Thus far it is not known whether a BCI system can be developed that utilizes the states of brain structures that are situate...

After suffering a more severe disease like spinal cord injury or stroke patients are often not able to interact or even communicate with their environment anymore, especially at the beginning of rehabilitation. Brain-computer interfaces (BCIs) can substitute this temporarily lost communication channels and might support rehabilitation by providing...

Brain-computer interfaces (BCI) are mostly realized using the P300, motor imagery or steady-state visually evoked potentials (SSVEP) measured with the electroencephalogram (EEG) to control external devices. The EEG is measured non-invasively with electrodes mounted on the human scalp using conductive electrode gel for optimal impedance and data qua...

After suffering from a severe disease like spinal cord injury or stroke, patients are often unable to interact or even communicate with their environment anymore, especially at the beginning of rehabilitation. Brain-computer interfaces (BCIs) can substitute these temporarily lost communication channels. They also might support rehabilitation by pro...

This chapter introduces the current state of the art of brain—computer interface (BCI) technology based on noninvasive surface electroencephalogram (EEG) recordings. The basic idea of a BCI is to enable a new communication channel that bypasses the standard neural pathways and output channels in order to control an external device. The ultimate goa...

Brain-computer interfaces (BCIs) are rapidly developing into a mainstream, worldwide research endeavor. With so many new groups and projects, it can be difficult to identify the best ones. This book summarizes ten leading projects from around the world. About 60 submissions were received in 2011 for the highly competitive BCI Research Award, and an...

The first commercial brain–computer interface environment has been developed so research centers could easily and quickly run BCI experiments to test algorithms and different strategies. A first BCI system was available on the market in 1999, and was continuously improved to the system available today, which is now used in more than 60 countries wo...

A brain computer interface (BCI) using steady state visual evoked potentials (SSVEP) is presented. EEG was derived from 3 subjects to test the suitability of SSVEPs for robot control. To calculate features and to classify the EEG data Minimum Energy and Fast Fourier Transformation (FFT) with linear discriminant analysis (LDA) were used. Finally the...

An electroencephalogram (EEG) based brain-computer interface (BCI) was connected with a Virtual Reality system in order to control a smart home application. Therefore special control masks were developed which allowed using the P300 component of the EEG as input signal for the BCI system. Control commands for switching TV channels, for opening and...

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...

(22) g.tec Guger Technologies OEG, Herbersteinstrasse 60, 8020 Graz, (23) Universitat Politècnica de Catalunya, Barcelona, Spain (24) Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain Abstract A brain-computer interface (BCI) is a new communication channel between the human brain and a digital computer. Such systems have be...

A brain-computer interface (BCI) is a new communication channel between the human brain and a digital computer. The ambitious goal of a BCI is finally the restoration of movements, communication and environmental control for handicapped people. However, in more recent research also BCI control in combination with Virtual Environments (VE) gains mor...

Place cells are located in the hippocampus of the brain and play an important role for spatial navigation. In this study neural spike activity of freely moving rats along with the position of the rats was acquired. The study was performed to investigate if position reconstruction is possible if the rat is freely moving in open arenas with and witho...

An electroencephalogram (EEG) based brain-computer interface (BCI) was connected to a virtual reality (VR) system in order to control a smart home application. Therefore special control masks were developed which allowed using the P300 component of the EEG as input signal for the BCI system. Control commands for switching TV channels, for opening a...

A n electroencephalogram (EEG) based brain-computer interface (BCI) was connected with a Virtual Reality system in order to control a smart home application. Therefore special control masks were developed which allowed using the P300 component of the EEG as input signal for the BCI system. Control commands for switching TV channels, for opening and...

A brain-computer interface (BCI) is a new communication channel between the human brain and a digital computer. Furthermore a BCI enables communication without using any muscle activity for a subject. The ambitious goal of a BCI is finally the restoration of movements, communication and environmental control for handicapped people. However, in more...

Place cells are located in the hippocampus of the brain and play an important role for spatial navigation. In this study neural spike activity of freely moving rats along with the position of the rats was acquired. The study was performed to investigate if position reconstruction is possible if the rat is freely moving in open arenas of different s...

Monitoring of neural function in newborns may enable the early prediction of the long-term neurodevelopmental outcome of infants. Artefacts, like eye movements or muscular artefacts are common during long-term recording of neural activity and may lead to erroneous results. Fourier analysis, wavelet analysis and principal component analysis (PCA) ar...

In order to describe how high altitude affects the body during a one night stay at 4000m experiments were performed in a hypobaric chamber and compared to a study on Dachstein (mountain in Austria, 2700m). Ten subjects had to perform a reaction time task at different altitudes. The EEG and ECG were recorded simultaneously. Additionally, the oxygen...

Abstract An experiment was conducted,in a Cave-like environment,to explore the relationship between physiological responses and each of breaks in presence, and utterances by virtual characters towards the participants. Twenty people explored a virtual environment,(VE) that depicted a virtual bar scenario. The experiment,was divided into a training...

In the Eastern Alps, the Dachstein massif with a height of almost 3000 m is an ideal location for investigating the effects of changes in altitude on the human body. Within a few minutes, a cable car facilitates an ascent from 1702 m to 2700 m above sea level, where the partial pressure of oxygen is about 550mmHg (as compared to 760mmHg at sea leve...

In the Eastern Alps, the Dachstein massif with a height of almost 3000 m is an ideal location for investigating the effects of changes in altitude on the human body. A cable car allows an ascent within a few minutes to 2700 m, where the partial pressure of oxygen is about 550 mm of mercury compared to 760 mm at sea level. Ten healthy subjects perfo...

An EEG-based brain computer interface (BCI) system converts brain activity into control signals. A BCI system has to satisfy different demands depending on the application area. A laboratory PC based system allows the flexible design of multiple/single channel feature extraction, classification methods and experimental paradigms. The key advantage...

In this study, ten healthy subjects performed a reaction time task at 990 m and 2700 m in altitude. The subjects were instructed to perform a right hand index finger movement as fast as possible after a green light flashed (repeated 50 times). The corresponding electrocardiogram (ECG) and the electroencephalogram (EEG) were recorded. From the ECG h...

In the Eastern Alps, the Dachstein massif with a height of almost 3000 m is an ideal location for investigating the effects of changes in altitude on the human body. Within a few minutes, a cable car facilitates an ascent from 1702 to 2700 m above sea level, where the partial pressure of oxygen is about 550 mmHg (as compared to 760 mmHg at sea leve...

In the Eastern Alps in Europe, the Dachstein. massif with a height of almost 3000 m is an ideal location for investigating the effects of changes in altitude on the human body. Within a few minutes, a cable car facilitates an ascent from 1702 m to 2700 m above sea level, where the partial pressure of oxygen is about 550 mmHg (as compared to 760 mmH...

EEG-based brain-computer interface (BCI) systems convert brain activity into control signals and have been developed for people with severe disabilities to improve their quality of life. A BCI system has to satisfy different demands depending on the application area. A laboratory PC based system allows the flexible design of multiple/single channel...

EEG-based brain computer interface (BCI) systems measure brain activity in order to control a device just by thoughts. There are different demands depending on the application area. A PC based system allows the flexible design of feature extraction, classification methods and experimental paradigms. The key advantage of a Pocket PC based approach i...

Abstract Beside standard questionnaires physiological measures can be used ,to describe the state of Presence in a virtual environment. A total of 21 participants explored a virtual bar in a CAVE like system. The experiment was divided into a baseline-, training- and experimental phase. During the experimental phase breaks in presence (BIPS) in for...

Ninety-nine healthy people participated in a brain-computer interface (BCI) field study conducted at an exposition held in Graz, Austria. Each subject spent 20-30 min on a two-session BCI investigation. The first session consisted of 40 trials conducted without feedback. Then, a subject-specific classifier was set up to provide the subject with fee...

A Brain-Computer Interface (BCI) is designed based on a Rapid Prototyping environment which enables a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. The system is able to process multiple EEG channels on-line and operates under Windows in real-time on a standard PC. Th...

We investigated the EEG beta event-related synchronization (ERS) after tactile finger stimulation in three subjects. Prior studies from our group using electrical stimulation and self-paced movement showed a beta rebound within one second after stimulation respectively movement offset. As the tactile-stimulation-data showed a similar ERS behaviour,...

We investigated the EEG beta event-related synchronization (ERS) after tactile finger stimulation in three subjects. Prior studies from our group using electrical stimulation and self-paced movement showed a beta rebound within one second after stimulation respectively movement offset. As the tactile-stimulation-data showed a similar ERS behaviour,...

Oscillatory cortical activity in the beta frequency range (14–32 Hz) was investigated in a voluntary movement task using closely-spaced electroencephalogram recordings over the sensorimotor cortex. According to recent studies, short-lasting beta oscillations were observed within the first second after termination of a self-paced finger movement. In...

The analytic solution of the harmonic downward continuation of the scalp potential field in an N-shell heterogeneous, but isotropic, spherical volume conductor model has been derived. The objective of this paper was to investigate the realization of a so-called "high-resolution electroencephalogram (EEG)": by enhancing the poor spatial resolution o...

The application of surface laplacian and linear estimation methods to single trial EEG data was studied. EEG was recorded in 3 subjects during voluntary, self-paced extensions and flexions of the index finger. In each subject a post-movement beta synchronisation was found in specific frequency bands. The surface laplacian estimates were calculated...

The objective of this paper is to combine spatially enhanced event-related desynchronization (ERD) data recorded during motor imagery experiments to the anatomy of the brain. Four methods available, the local average reference method (LAR), the surface Laplacian method (LP), the linear estimation method (LE) and the analytical de-blurring method (A...

In this paper we present a study of spline surface Laplacian (LP), linear estimation (LE) and analytical deblurring (AD) utilized to improve the spatial resolution of single trial EEG data. AD is a method to reconstruct the potential distribution on the cortical surface. The dependency of AD on the electrode grid size as well as the sensitivity to...

Spontaneous EEG can display spatio-temporal patterns of desynchronized or synchronized alpha band activity. Event-related desynchronization (ERD) of rhythms within alpha and lower beta bands is characteristic of activated cortical areas ready to process information or to prepare a movement, while event-related synchronization (ERS) in the same freq...