A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals
Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending
commands to the external world using the electroencephalographic activity or other …
commands to the external world using the electroencephalographic activity or other …
Multiple neural spike train data analysis: state-of-the-art and future challenges
Multiple electrodes are now a standard tool in neuroscience research that make it possible
to study the simultaneous activity of several neurons in a given brain region or across …
to study the simultaneous activity of several neurons in a given brain region or across …
Bayesian population decoding of motor cortical activity using a Kalman filter
W Wu, Y Gao, E Bienenstock, JP Donoghue… - Neural …, 2006 - direct.mit.edu
Effective neural motor prostheses require a method for decoding neural activity representing
desired movement. In particular, the accurate reconstruction of a continuous motion signal is …
desired movement. In particular, the accurate reconstruction of a continuous motion signal is …
A comprehensive survey of brain interface technology designs
In this work we present the first comprehensive survey of Brain Interface (BI) technology
designs published prior to January 2006. Detailed results from this survey, which was based …
designs published prior to January 2006. Detailed results from this survey, which was based …
Rapid adaptation of brain–computer interfaces to new neuronal ensembles or participants via generative modelling
For brain–computer interfaces (BCIs), obtaining sufficient training data for algorithms that
map neural signals onto actions can be difficult, expensive or even impossible. Here we …
map neural signals onto actions can be difficult, expensive or even impossible. Here we …
Unscented Kalman filter for brain-machine interfaces
Brain machine interfaces (BMIs) are devices that convert neural signals into commands to
directly control artificial actuators, such as limb prostheses. Previous real-time methods …
directly control artificial actuators, such as limb prostheses. Previous real-time methods …
Modeling and decoding motor cortical activity using a switching Kalman filter
We present a switching Kalman filter model for the real-time inference of hand kinematics
from a population of motor cortical neurons. Firing rates are modeled as a Gaussian mixture …
from a population of motor cortical neurons. Firing rates are modeled as a Gaussian mixture …
Evaluation criteria for BCI research
A Schlögl, J Kronegg, JE Huggins, SG Mason - 2007 - direct.mit.edu
To analyze the performance of BCI systems, some evaluation criteria must be applied. The
most popular is accuracy or error rate. Because of some strict prerequisites, accuracy is not …
most popular is accuracy or error rate. Because of some strict prerequisites, accuracy is not …
Information systems opportunities in brain–machine interface decoders
Brain-machine interface (BMI) systems convert neural signals from motor regions of the
brain into control signals to guide prosthetic devices. The ultimate goal of BMIs is to improve …
brain into control signals to guide prosthetic devices. The ultimate goal of BMIs is to improve …
Recording and decoding for neural prostheses
This paper reviews technologies and signal processing algorithms for decoding peripheral
nerve and electrocorticogram signals to interpret human intent and control prosthetic arms …
nerve and electrocorticogram signals to interpret human intent and control prosthetic arms …