AI Medical Compendium Topic:
Brain-Computer Interfaces

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Day-to-day variability in hybrid, passive brain-computer interfaces: comparing two studies assessing cognitive workload.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
As hybrid, passive brain-computer interface systems become more advanced, it is important to grow our understanding of how to produce generalizable pattern classifiers of physiological data. One of the most difficult problems in applying machine lear...

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine.

The Review of scientific instruments
Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of ...

Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier.

Biomedizinische Technik. Biomedical engineering
There is general agreement in the brain-computer interface (BCI) community that although non-linear classifiers can provide better results in some cases, linear classifiers are preferable. Particularly, as non-linear classifiers often involve a numbe...

Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence
Recent trends in image understanding have pushed for scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape analysis, contextual reasoning, and local appearance based classifiers. In this...

Investigating deep learning for fNIRS based BCI.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Functional Near infrared Spectroscopy (fNIRS) is a relatively young modality for measuring brain activity which has recently shown promising results for building Brain Computer Interfaces (BCI). Due to its infancy, there are still no standard approac...

Online control of a humanoid robot through hand movement imagination using CSP and ECoG based features.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Intention recognition through decoding brain activity could lead to a powerful and independent Brain-Computer-Interface (BCI) allowing for intuitive control of devices like robots. A common strategy for realizing such a system is the motor imagery (M...

EEG error potentials detection and classification using time-frequency features for robot reinforcement learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In thought-based steering of robots, error potentials (ErrP) can appear when the action resulting from the brain-machine interface (BMI) classifier/controller does not correspond to the user's thought. Using the Steady State Visual Evoked Potentials ...

An EEG/EOG-based hybrid brain-neural computer interaction (BNCI) system to control an exoskeleton for the paralyzed hand.

Biomedizinische Technik. Biomedical engineering
The loss of hand function can result in severe physical and psychosocial impairment. Thus, compensation of a lost hand function using assistive robotics that can be operated in daily life is very desirable. However, versatile, intuitive, and reliable...

Combining human volitional control with intrinsic controller on robotic prosthesis: A case study on adaptive slope walking.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Affording lower-limb amputees the ability to volitionally control robotic prostheses can improve the adaptability to terrain changes as well as enhancing proprioception. However, it also increases amputees' conscious burdens for prosthesis control. T...

A robo-pigeon based on an innovative multi-mode telestimulation system.

Bio-medical materials and engineering
In this paper, we describe a new multi-mode telestimulation system for brain-microstimulation for the navigation of a robo-pigeon, a new type of bio-robot based on Brain-Computer Interface (BCI) techniques. The multi-mode telestimulation system overc...