A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives

I Choi, I Rhiu, Y Lee, MH Yun, CS Nam - PloS one, 2017 - journals.plos.org
A new Brain-Computer Interface (BCI) technique, which is called a hybrid BCI, has recently
been proposed to address the limitations of conventional single BCI system. Although some …

Non-invasive control interfaces for intention detection in active movement-assistive devices

J Lobo-Prat, PN Kooren, AHA Stienen… - … of neuroengineering and …, 2014 - Springer
Active movement-assistive devices aim to increase the quality of life for patients with
neuromusculoskeletal disorders. This technology requires interaction between the user and …

Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

A Biasiucci, R Leeb, I Iturrate, S Perdikis… - Nature …, 2018 - nature.com
Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals
into intended movements of the paralyzed limb. However, the efficacy and mechanisms of …

Noninvasive brain-computer interfaces based on sensorimotor rhythms

B He, B Baxter, BJ Edelman, CC Cline… - Proceedings of the …, 2015 - ieeexplore.ieee.org
Brain-computer interfaces (BCIs) have been explored in the field of neuroengineering to
investigate how the brain can use these systems to control external devices. We review the …

The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

S Perdikis, L Tonin, S Saeedi, C Schneider… - PLoS …, 2018 - journals.plos.org
This work aims at corroborating the importance and efficacy of mutual learning in motor
imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our …

Towards independence: a BCI telepresence robot for people with severe motor disabilities

R Leeb, L Tonin, M Rohm, L Desideri… - Proceedings of the …, 2015 - ieeexplore.ieee.org
This paper presents an important step forward towards increasing the independence of
people with severe motor disabilities, by using brain-computer interfaces to harness the …

Towards noninvasive hybrid brain–computer interfaces: framework, practice, clinical application, and beyond

G Müller-Putz, R Leeb, M Tangermann… - Proceedings of the …, 2015 - ieeexplore.ieee.org
In their early days, brain-computer interfaces (BCIs) were only considered as control
channel for end users with severe motor impairments such as people in the locked-in state …

A brain-controlled exoskeleton with cascaded event-related desynchronization classifiers

K Lee, D Liu, L Perroud, R Chavarriaga… - Robotics and Autonomous …, 2017 - Elsevier
This paper describes a brain–machine interface for the online control of a powered lower-
limb exoskeleton based on electroencephalogram (EEG) signals recorded over the user's …

Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review

LR Quitadamo, F Cavrini, L Sbernini… - Journal of neural …, 2017 - iopscience.iop.org
Support vector machines (SVMs) are widely used classifiers for detecting physiological
patterns in human–computer interaction (HCI). Their success is due to their versatility …

Learning to control a BMI-driven wheelchair for people with severe tetraplegia

L Tonin, S Perdikis, TD Kuzu, J Pardo, B Orset, K Lee… - Iscience, 2022 - cell.com
Mind-controlled wheelchairs are an intriguing assistive mobility solution applicable in
complete paralysis. Despite progress in brain-machine interface (BMI) technology, its …