Publications by Robert Leeb | EPFL Graph Search

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Objective. This work presents a first motor imagery-based, adaptive brain–computer interface (BCI) speller, which is able to exploit application-derived context for improved, simultaneous classifier adaptation and spelling. Online spelling experiments with ...

In this paper we show how healthy subjects can operate a non-invasive asynchronous BCI for controlling a FES neuroprosthesis and manipulate objects to carry out daily tasks in ecological conditions. Both, experienced and novel subjects proved to be able to ...

The non-invasive Brain-Computer Interface (BCI) developed in our lab targets asynchronous operation of devices by monitoring electroencephalographic (EEG) activity and identifying oscillatory patterns that the user can voluntary modulate through the execut ...

Brain-machine interfaces (BMI) have largely been demonstrated in laboratory conditions involving, mainly, healthy users. We have recently carried out a series of studies with a substantial number of motor-disabled end-users operating different brain-contro ...

In this paper we present the results of six motor-disabled patients manoeuvring a telepresence robot via a BCI. Remarkably, although five of the patients had never visited the location where the telepresence robot was operating, they achieved similar perfo ...

Controlling a device via a brain-computer interface (BCI) requires the participant to look and to split the attention between the device and the BCI feedback, which is partly contradictory. Therefore, a stimulation system based on 6 coin-motors is develope ...

Transcranial Direct Current Stimulation (tDCS) has been shown to selectively modulate cortical responses in memory, motor and perceptual tasks. Here we show that this type of stimulation results in targeted enhancement of brain patterns elicited during mot ...

Recently, several studies have started to explore covert visuospatial attention as a control signal for brain–computer interfaces (BCIs). Covert visuospatial attention represents the ability to change the focus of attention from one point in the space with ...

We have integrated the Graz brain-computer interface (BCI) system with a highly immersive virtual reality (VR) Cave-like system. This setting allows for a new type of experience, whereby participants can control a virtual world using imagery of movement. H ...

Brain-computer interfaces (BCI) have been shown to be a promising tool in rehabilitation and assistive scenarios. Within these contexts, brain signals can be decoded and used as commands for a robotic device, allowing to translate user’s intentions into mo ...

Brain-Computer Interfaces (BCIs) can be extended by other input signals to form a so-called hybrid BCI (hBCI). Such an hBCI allows the processing of several input signals with at least one brain signal for control purposes, i.e. communication and environme ...

We describe a multi-modal brain-computer interface (BCI) experiment, situated in a highly immersive CAVE. A subject sitting in the virtual environment controls the main character of a virtual reality game: a penguin that slides down a snowy mountain slope. ...

Objective: This study investigated the effect of multimodal (visual and auditory) continuous feedback with information about the uncertainty of the input signal on motor imagery based BCI performance. A liquid floating through a visualization of a funnel ( ...

The prospect of controlling devices merely by the power of one’s thoughts is compelling, especially for assistive technology applications. In the accompanying video, we show how we have strived to push brain–computer interface (BCI) technology out of the l ...

The aim of this work is to present the development of a hybrid Brain-Computer Interface (hBCI) which combines existing input devices with a BCI. Thereby, the BCI should be available if the user wishes to extend the types of inputs available to an assistive ...

One important source of performance degradation in BCIs is bias towards one of the mental classes. Recent literature has focused on the general problem of classification accuracy drop, identifying non-stationarity as the generating factor, thus leading to ...

Controlling a brain-actuated device requires the participant to look at and to split his attention between the interaction of the device with its environment and the status information of the Brain-Computer Interface (BCI). Such parallel visual tasks are p ...

Brain-Computer Interfaces convey a great potential in the field of stroke rehabilitation, where the continuous monitoring of the execution of mental tasks could support the positive effects of the therapy by reinforcing specific mental patterns. We propose ...

Brain-Computer Interfaces (BCIs) have been successfully used to control assistive mobility devices (like a telepresence robot or an electric wheelchair) using only motor imagery. Importantly, disabled end-users are able to achieve similar performances as h ...

Brain-Computer Interfaces (BCIs) provide a mean to access the damaged motor network of the brain after stroke, and could be used to drive and promote beneficial plasticity. Among the available therapeutic approaches, Functional Electrical Stimulation (FES) ...

Robert Leeb

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Context-aware adaptive spelling in motor imagery BCI

Towards Natural Non-Invasive Hand Neuroprostheses for Daily Living

Evidence Accumulation in asynchronous BCI

Brain-Machine Interfaces: Progress in Large Clinical Validation

BCI Telepresence: A Six Patient Evaluation

Feel the BCI vibe – vibrotactile BCI feedback

Selective Enhancement of Motor Imagery Features Using Transcranial Direct Current Stimulation

Time-Dependent Approach for Single Trial Classification of Covert Visuospatial Attention

Human-Computer Interface Issues in Controlling Virtual Reality With Brain-Computer Interface

Detecting intention to grasp during reaching movements from EEG

The hybrid Brain-Computer Interface: a bridge to assistive technology?

Thinking Penguin: Multi-modal Brain-Computer Interface Control of a VR Game

The effect of multimodal and enriched feedback on SMR-BCI performance

The Birth of the Brain–Controlled Wheelchair

Tools for brain-computer interaction: a general concept for a hybrid BCI

A supervised recalibration protocol for unbiased BCI

Freeing the visual channel by exploiting vibrotactile BCI feedback

EEG Microstates for BCI Therapist Feedback: Preliminary Results on a Stroke Patient

Brain-Actuated Assistive Mobility For Disabled End-User

Motor Recovery After Stroke by Means of BCI-Guided Functional Electrical Stimulation