BCI@LU is the research group at Lund University focusing on understanding the brain when it comes to Passive, Active and Reactive Brain-Computer Interfaces. The human brain is complex, and to succeed in understanding it we need to approach it interdisciplinary. The group consists of ~15 Professors, Post-Docs and PhD students from the Department of Automatic Control, the Department of Psychology and Department of Mathematical Statistics at Lund University. If you're a researcher at Lund University with similar interests, feel free to join our group.

2023

Johanna Wilroth, Bo Bernhardsson, Frida Heskebeck, Martin A Skoglund, Carolina Bergeling and Emina Alickovic: Improving EEG-based decoding of the locus of auditory attention through domain adaptation

Tanveer, M Asjid: Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation

Martin Gemborn Nilsson, Pex Tufvesson, Frida Heskebeck and Mikael Johansson: An open-source human-in-the-loop BCI research framework: method and design

Pex Tufvesson, Martin Gemborn Nilsson, Kristian Soltesz and Bo Bernhardsson: Real-time Bayesian Control of Reactive Brain Computer Interfaces.
 

2022

Frida Heskebeck, Carolina Bergeling, and Bo Bernhardsson: Multi-Armed Bandits in Brain-Computer Interfaces

Emma Fallenius and Linda Karlsson: Tensor Decompositions of EEG Signals for Transfer Learning Applications

Julia Adlercreutz: Brainstem response estimation using continuous sound - A feasibility study

Viktor Andersson and Nelly Ostréus: Speech activity detection in videos

Sara Enander and Louise Karsten: Computation models for audiovisual attention decoding
 

2021

Maria Sandsten, Rachele Anderson, Isabella Reinhold, Bo Bernhardsson, Carolina Bergeling and Mikael Johansson: A Novel Multitaper Reassignment Method for Estimation of Phase Synchrony

Frida Heskebeck and Carolina Bergeling: An Adaptive Approach for Task-Driven BCI Calibration

Oskar Keding and David Ohlin: Statistics and Machine Learning for Classification of Emotional and Semantic Content of EEG

Tom Andersen: Implementation of a Simple Asynchronous Pipeline Framework (SAPF) for construction of real-time BCI systems
 

2020

Maria Sandsten and Rachele Anderson: Time-frequency feature extraction for classification of episodic memory

Johanna Wilroth: Domain Adaptation for Attention Steering
 

2018

Damir Basic Knezevic and Albin Heimerson: Statistical and machine learning methods for classification of episodic memory