Publications by Robert Leeb | EPFL Graph Search

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This work studies the class of algorithms for learning with side-information that emerges by extending generative models with embedded context-related variables. Using finite mixture models (FMMs) as the prototypical Bayesian network, we show that maximum- ...

In this paper, the results of a pilot interview study with 19 subjects participating in an EEG-based non-invasive brain–computer interface (BCI) research study on stroke rehabilitation and assistive technology and of a survey among 17 BCI professionals are ...

During the last years, several studies have suggested that Brain-Computer Interface (BCI) can play a critical role in the field of motor rehabilitation. In this case report, we aim to investigate the feasibility of a covert visuospatial attention (CVSA) dr ...

OBJECTIVES: Brain-computer interfaces (BCIs) are no longer only used by healthy participants under controlled conditions in laboratory environments, but also by patients and end-users, controlling applications in their homes or clinics, without the BCI exp ...

To patients who have lost the functionality of their hands as a result of a severe spinal cord injury or brain stroke, the development of new techniques for grasping is indispensable for reintegration and independency in daily life. Functional Electrical S ...

Non–Invasive Brain–Computer Interfaces (BCI) convey a great potential in the field of stroke rehabilitation, where the continuous monitoring of mental tasks execution could support the positive effects of standard therapies. In this paper we combine time-f ...

This paper summarizes two novel ways to extend brain-computer interface (BCI) systems. One way involves hybrid BCIs. A hybrid BCI is a system that combines a BCI with another device to help people send information. Different types of hybrid BCIs are discus ...

In recent years, new research has brought the field of electroencephalogram (EEG)-based brain–computer interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, key ...

Hybrid Brain-Computer Interfaces (BCI) are representing a recent approach to develop practical BCIs. In such a system disabled users are able to use all their remaining functionalities as control possibilities in parallel with the BCI. Sometimes these peop ...

One of the challenges of using brain-computer interfaces (BCIs) over extended periods of time is the variation of the users' performance across different experimental days. The goal of the current study is to propose a performance estimator for an electroe ...

This paper presents an important step forward towards increasing the independence of people with severe motor disabilities, by using brain-computer interfaces (BCI) to harness the power of the Internet of Things. We analyze the stability of brain signals a ...

Successful operation of motor imagery (MI)-based brain-computer interfaces (BCI) requires mutual adaptation between the human subject and the BCI. Traditional training methods, as well as more recent ones based on co-adaptation, have mainly focused on the ...

This paper discusses a time-dependent classification approach for single trial recognition of spatial covert visual attention for Brain–Computer Interface. Covert visual attention is a natural and intuitive mental task that does not require any external st ...

In this paper we propose a method to modulate the level of assistance provided by a shared controller, not only given the environmental context, but also according to the context of the user’s current behaviour. We show that the enhanced situational contex ...

Brain-Computer Interfaces (BCIs) are no longer only used by healthy subjects under control conditions in laboratory environments, but by patients controlling applications at their homes, without the BCI experts around. But are the technology and the field ...

Objective. In this work we present—for the first time—the online operation of an electroencephalogram (EEG) brain–computer interface (BCI) system based on covert visuospatial attention (CVSA), without relying on any evoked responses. Electrophysiological c ...

Practical Brain-Computer Interfaces (BCIs) for disabled people should allow them to use all their remaining functionalities as control possibilities. Sometimes these people have residual activity of their muscles, most likely in the morning when they are n ...

In their early days, BCIs were only considered as control channel for end users with severe motor impairments such as people in the locked-in state. But, thanks to the multidisciplinary progress achieved over the last decade, the range of BCI applications ...

Motor imagery (MI) brain-computer interfaces (BCIs) translate a subject’s motor intention to a command signal. Most MI BCIs use power features in the mu or beta rhythms, while several results have been reported using a measure of phase synchrony, the phase ...

The Fifth International Brain-Computer Interface (BCI) Meeting met on 3rd June 2013 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 19 workshops covering topics in brain-computer interface and brain-machine inter ...

Robert Leeb

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Context-Aware Learning for Generative Models

Psychosocial and Ethical Aspects in Non-Invasive EEG-Based BCI Research — A Survey Among BCI Users and BCI Professionals

Behavioral and cortical effects during attention driven brain-computer interface operations in spatial neglect: A feasibility case study

Transferring brain-computer interfaces beyond the laboratory: Successful application control for motor-disabled users

On The Road To A Neuroprosthetic Hand: A Novel Hand Grasp Orthosis Based on Functional Electrical Stimulation

Combining Discriminant and Topographic Information in BCI: Preliminary Results on Stroke Patients

Toward smarter BCIs: extending BCIs through hybridization and intelligent control

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

A hybrid BCI based on the fusion of EEG and EMG activities

Adaptive Assistance for Brain-Computer Interfaces by Online Prediction of Command Reliability

Towards Independence: A BCI Telepresence Robot for People with Severe Motor Disabilities

Subject-oriented training for motor imagery brain-computer interfaces

Single trial detection of spatial covert visual attention for BCI

Online Modulation of the Level of Assistance in Shared Control Systems

Are we ready? Issues in transferring BCI technology from experts to users

An online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation

Multimodal Fusion of Muscle and Brain Signals for a Hybrid-BCI

Towards non-invasive hybrid brain-computer interfaces: Framework, practice, clinical application and beyond

Phase-based features for Motor Imagery Brain-Computer Interfaces

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future