In this chapter, we give an overview of the Graz-BCI research, from the classic motor
imagery detection to complex movement intentions decoding. We start by describing the …

Electrical signals encoding different forms of information can be observed at multiple levels
of the human nervous system. Typically, these signals have been recorded in a rather …

Several works have reported on the reconstruction of 2D/3D limb kinematics from low-
frequency EEG signals using linear regression models based on positive correlation values …

A brain-computer interface (BCI) can help to overcome movement deficits in persons with
spinal-cord injury. Ideally, such a BCI detects detailed movement imaginations, ie …

Background One of the current challenges in brain-machine interfacing is to characterize
and decode upper limb kinematics from brain signals, eg to control a prosthetic device …

Objective. One of the main goals in brain–computer interface (BCI) research is the
replacement or restoration of lost function in individuals with paralysis. One line of research …

One of the current challenges in human motor rehabilitation is the robust application of Brain-
Machine Interfaces to assistive technologies such as powered lower limb exoskeletons …

The past decades have seen the rapid development of upper limb kinematics decoding
techniques by performing intracortical recordings of brain signals. However, the use of non …

A motion trajectory prediction (MTP)-based brain–computer interface (BCI) aims to
reconstruct the three-dimensional (3D) trajectory of upper limb movement using …

Tracking hand movements during number tasks has become a powerful method for
disentangling competing models of numerical representation. In two experiments …