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Introduction
Christoph Guger is running g.tec medical engineering in Austria, Spain, the US and Hong Kong and is developing brain-computer interfaces for non-invasive and invasive applications.
Additional affiliations
January 1999 - present
January 1997 - December 2000
Technische Universität Graz
Description
- Development of real-time brain-computer interface.
Publications
Publications (414)
This article investigated the automatic recognition of felt and musically communicated emotions using electroencephalogram (EEG), electrocardiogram (ECG), and acoustic signals, which were recorded from eleven musicians instructed to perform music in order to communicate happiness, sadness, relaxation, and anger. Musicians' self-reports indicated th...
Stroke is a major cause of mortality worldwide, disrupts cerebral blood flow, leading to severe brain damage. Hemiplegia, a common consequence, results in motor task loss on one side of the body. Many stroke survivors face long-term motor impairments and require great rehabilitation. Electroencephalograms (EEGs) provide a non-invasive method to mon...
Background:
Intraoperative functional mapping for glioma resection often necessitates awake craniotomies, requiring active patient participation. This procedure presents challenges for both the surgical team and the patient. Thus, minimizing mapping time becomes crucial. Passive mapping utilizing electrocorticography (ECoG) presents a promising ap...
Brain mapping is vital in understanding the brain’s functional organization. Electroencephalography (EEG) is one of the most widely used brain mapping approaches, primarily because it is non-invasive, inexpensive, straightforward, and effective. Increasing the electrode density in EEG systems provides more neural information and can thereby enable...
Introduction
Brain-computer interfaces (BCIs) based on functional electrical stimulation have been used for upper extremity motor rehabilitation after stroke. However, little is known about their efficacy for multiple BCI treatments. In this study, 19 stroke patients participated in 25 upper extremity followed by 25 lower extremity BCI training ses...
Graphene-enabled micro-transistor arrays can be used to improve our understanding of how infraslow brain signals relate to changes in cerebral blood flow.
Background
Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)–guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties.
Objectives
The purpose of this study was to establish whet...
Objective: Recent trends in brain-computer interface (BCI) research concern the passive monitoring of brain activity, which aim to monitor a wide variety of cognitive states. Engagement is such a cognitive state, which is of interest in contexts such as learning, entertainment or rehabilitation. This study proposes a novel approach for real-time es...
The first chapter of this book readers introduced BCIs, the BCI Award Foundation and 2022 jury, the procedures and criteria of the awards, and the 12 nominees in 2022. Most chapters described projects that were nominated for a BCI Research Award. This is the last chapter of the book. Here, we provide more information about the awards ceremony and t...
With brain-computer interfaces (BCIs), people can send information directly from their brains to computers. People can use BCIs to send messages or commands without moving. In 2010, we launched the Annual BCI Research Awards. People submit their projects to a jury that scores each project on many criteria and then selects the best projects from tha...
Graphene-based solution-gated field-effect transistors (gSGFETs) allow the quantification of the brain's full-band signal. Extracellular alternating current (AC) signals include local field potentials (LFP, population activity within a reach of hundreds of micrometers), multiunit activity (MUA), and ultimately single units. Direct current (DC) pote...
Background
Electrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We...
In the past decades, brain–computer interfaces (BCIs) have been among the fastest-growing technologies and a very prolific research field. Typically, sending input to a computer requires the user to use their hands (e.g., for controlling the mouse and keyboard), their eyes (e.g., in gaze tracking), or realize some type of physical action. On the co...
INTRODUCTION: In hypertrophic cardiomyopathy (HCM), ventricular arrhythmia associates with severity of LVH and scar, and presence vs absence of a sarcomeric gene mutation (G+LVH+ vs G-LVH+). Also, ECG changes in subclinical HCM (G+LVH-) signal increased risk of phenotype progression.
HYPOTHESES: ECG Imaging (ECGI) can detect: i) subtle electrophysi...
In this study, a few-shot transfer learning approach was introduced to decode movement intention from electroencephalographic (EEG) signals, allowing to recognize new tasks with minimal adaptation. To this end, a dataset of EEG signals recorded during the preparation of complex sub-movements was created from a publicly available data collection. Th...
The use of Brain–Computer Interfaces (BCI) as rehabilitation tools for chronically ill neurological patients has become more widespread. BCIs combined with other techniques allow the user to restore neurological function by inducing neuroplasticity through real-time detection of motor-imagery (MI) as patients perform therapy tasks. Twenty-five stro...
Patients with locked-in syndrome (LIS) and complete locked-in syndrome (CLIS) own a fully functional brain restricted within a non-functional body. In order to help LIS patients stay connected with their surroundings, brain-computer interfaces (BCIs) and related technologies have emerged. BCIs translate brain activity into actions that can be perfo...
Introduction
Electrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly...
Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interaction. The coupling of robot assisted gait training (RAGT) with a brain-machine interface (BMI) represents an important step in this direction but requires better elucidation of the effect of RAGT on the user's neural modulation. Here, we investigated ho...
Brain-computer interfaces (BCIs) are systems that use direct real-time recordings of brain activity for communication and control. This chapter introduces the current state of the art of noninvasive and invasive BCIs. We start with a brief conceptual overview, discuss different types of input signals, and outline common control signals with some ty...
In this paper, a novel Electroepncephalography (EEG)-based Brain Computer Interface (BCI) approach is proposed to decode motion intention from EEG signals collected at the scalp of subjects performing motor execution tasks. The impact of such systems, generally based on the ability to discriminate between the imagination of right/left hand movement...
Brain-Computer Interface (BCI) technology enables users to operate external devices without physical movement. Electroencephalography (EEG) based BCI systems are being actively studied due to their high temporal resolution, convenient usage, and portability. However, fewer studies have been conducted to investigate the impact of high spatial resolu...
[This corrects the article DOI: 10.3389/fnins.2020.00582.].
Objective
Clinical assessment of consciousness relies on behavioural assessments, which have several limitations. Hence, disorder of consciousness (DOC) patients are often misdiagnosed. In this work, we aimed to compare the repetitive assessment of consciousness performed with a clinical behavioural and a Brain-Computer Interface (BCI) approach.
M...
Brain-Computer Interface (BCI) technology has been shown to provide new communication possibilities, conveying brain information externally. BCI-based robot control has started to play an important role, especially in medically assistive robots but not only there. For example, a BCI-controlled robotic arm can provide patients diagnosed with neurode...
Background
The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world’s longest running continued surveillance birth cohort providing a unique opportunity to u...
Mapping the entire frequency bandwidth of brain electrophysiological signals is of paramount importance for understanding physiological and pathological states. The ability to record simultaneously DC-shifts, infraslow oscillations (<0.1 Hz), typical local field potentials (0.1–80 Hz) and higher frequencies (80–600 Hz) using the same recording site...
The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering the breadth of topics in BCI (also called brain-machine interface) research. Some workshops provided detailed examinations of methods, hardware, o...
Stroke can cause severe motor and sensory impairments. Recent studies focus their attention to the Quantitative EEG (qEEG) searching for information in the brain signals that can help clinicians understating each patient’s clinical state. In this study, we recorded 8 min of resting state EEG to 34 stroke patients in order to find some correlation b...
Electrocorticogram (ECoG) well characterizes hand movement intentions and gestures. In the present work we aim to investigate the possibility to enhance hand pose classification, in a Rock-Paper-Scissor - and Rest - task, by introducing topological descriptors of time series data. We hypothesized that an innovative approach based on topological dat...
Many people who have had a stroke have trouble moving, even after therapy with the best experts and methods. New ways to make stroke therapy more effective could help people recover more effectively. Some research groups have developed brain-computer interface (BCI) systems that can measure when a stroke patient imagines hand movement by recording...
Brain–computer interface (BCI) technology has the potential to positively contribute to the educational learning environment, which faces many challenges and shortcomings. Cognitive and affective BCIs can offer a deep understanding of brain mechanisms, which may improve learning strategies and increase brain-based skills. They can offer a better em...
Mapping the entire frequency bandwidth of neuronal oscillations in the brain is of paramount importance for understanding physiological and pathological states. The ability to record simultaneously infraslow activity (<0.1 Hz) and higher frequencies (0.1-600 Hz) using the same recording electrode would particularly benefit epilepsy research. Howeve...
Disorders of consciousness include coma, unresponsive wakefulness syndrome (also known as vegetative state), and minimally conscious state. Neurobehavioral scales such as coma recovery scale-revised are the gold standard for disorder of consciousness assessment. Brain-computer interfaces have been emerging as an alternative tool for these patients....
We began this book with an introductory chapter so readers could understand more about BCIs and the annual procedures we follow to develop the awards and these books. The subsequent chapters of this book each presented a BCI project that was nominated for a BCI Research Award, with seven project summaries and four interviews. In the concluding chap...
Brain-computer interfaces (BCIs) enable users to send messages or commands directly through brain activity, without any movement. Most BCI systems aim to help persons with serious movement disabilities, but BCIs for consumer applications are increasingly prevalent. Each year since 2010, teams submitted their BCI projects to the BCI Research Awards,...
Stroke is the second foremost cause of death worldwide and is one of the most common causes of disability. Several approaches have been proposed to manage stroke patient rehabilitation such as robotic devices and virtual reality systems, and researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. There...
The vibro-tactile P300 based Brain-Computer Interface is an interesting tool for severe impaired patients which cannot communicate using the muscular and visual vias. In this study we presented an improved tactile BCI for binary communication that reduces the wrong answers by adding a threshold to the decision value to achieve a valid answer, other...
Introduction: Brain-computer interfaces (BCIs) provide a broad range of applications for human-computer interactions. Exploring cognitive control and underlying neurophysiological mechanisms brings essential contributions to this research field. In this paper, neurophysiological findings connected to cognitive control processes using the Stroop exp...
Description In this review article, we aimed to create a summary of the effects of internal variables on the performance of sensorimotor rhythm-based brain computer interfaces (SMR-BCIs). SMR-BCIs can be potentially used for interfacing between the brain and devices, bypassing usual central nervous system output, such as muscle activity. The carefu...
Description Sensorimotor rhythm-based brain-computer interfaces (SMR-BCIs) are used for the acquisition and translation of motor imagery-related brain signals into machine control commands, bypassing the usual central nervous system output. The selection of optimal external variable configuration can maximize SMR-BCI performance in both healthy and...
Brain–computer interfaces (BCIs) establish communication between a human brain and a computer or external devices by translating the electroencephalography (EEG) signal into computer commands. After stimulating a sensory organ, a positive deflection of the EEG signal between 250 and 700 ms can be measured. This signal component of the event-related...
Brain-computer interface (BCI) systems can provide communication and control without any physical movement. The BCI Research Awards are annual events to select the best BCI projects that year. Groups from around the world submit projects that are scored by a jury of international experts that selects twelve nominees and three winners. We also produ...
The introduction chapter of this book described the BCI Research Awards, selection criteria, nominees, and jury. Developing a good submission for a BCI Research Award is a formidable goal, and being nominated is even more demanding. This book has presented thirteen chapters by the authors of projects nominated for a BCI Research Award in 2019. Some...
Objective. The development of experimental methodology utilizing graphene micro-transistor arrays to facilitate and advance translational research into cortical spreading depression (CSD) in the awake brain. Approach. CSDs were reliably induced in awake nontransgenic mice using optogenetic methods. High-fidelity DC-coupled electrophysiological mapp...
Face recognition is impaired in patients with prosopagnosia, which may occur as a side effect of neurosurgical procedures. Face selective regions on the ventral temporal cortex have been localized with electrical cortical stimulation (ECS), electrocorticography (ECoG), and functional magnetic resonance imagining (fMRI). This is the first group stud...
Objective:
Development of experimental methodology utilising graphene micro-transistor arrays to facilitate and advance translational research into cortical spreading depression (CSD) in awake brain.
Approach:
CSDs were reliably induced in awake non-transgenic mice using optogenetic methods. High-fidelity DC-coupled electrophysiological mapping...
[This corrects the article DOI: 10.3389/fnins.2018.00514.].
Introduction
Numerous recent publications have explored Brain Computer Interfaces (BCI) systems as rehabilitation tools to help subacute and chronic stroke patients recover upper extremity movement. Recent work has shown that BCI therapy can lead to better outcomes than conventional therapy. BCI combined with other techniques such as Functional Ele...
The preceding nine chapters in this book presented an introduction and summaries of eight projects that were nominated for a BCI Research Award in 2018. In this chapter, we summarize the 2018 Awards Ceremony where we announced the three winning projects. We interviewed authors of these winning projects – Drs. Ajiboye, Tangermann, and Herff – and th...
The evaluation of the level of consciousness in patients with disorders of consciousness (DOC) is primarily based on behavioural assessments. Patients with unresponsive wakefulness syndrome (UWS) do not show any sign of awareness of their environment, while minimally conscious state (MCS) patients show reproducible but fluctuating signs of awarenes...
Objective
To evaluate whether introducing gamification in BCI rehabilitation of the upper limbs of post-stroke patients has a positive impact on their experience without altering their efficacy in creating motor mental images (MI).
Design
A game was designed purposely adapted to the pace and goals of an established BCI-rehabilitation protocol. Reh...
Introduction:Brain-computer interfaces have become an important tool in human computer interactions. The area of applications ranges from simple research to profound stroke therapy. In this paper, a novel approach to motor imagery is proposed. We analyzed left and right hand grasping using electroencephalography (EEG) and functional near-infrared s...
Introduction
Recent studies explored promising new quantitative methods to analyze electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG parameters, Brain Symmetry Index (BSI) and Laterality Coefficient (LC), with established functional scales for the stroke assessment.
Methods
Thirty-two healthy subjects and thirty-...
Brain-computer interfaces for user training and to extract biomarkers.
Background: Stroke is a disease with a high associated disability burden. Robotic-assisted gait training offers an opportunity for the practice intensity levels associated with good functional walking outcomes in this population. Neural interfacing technology, electroencephalography (EEG), or electromyography (EMG) can offer new strategies for robo...
The presentation shows the major principles and important components for building BCIs.
Questions and Answers of Day 5 of the Virtual Meeting