Towards cooperative brain-computer interfaces for space navigation

@inproceedings{Poli2013TowardsCB,
  title={Towards cooperative brain-computer interfaces for space navigation},
  author={Riccardo Poli and Caterina Cinel and Ana Matran-Fernandez and Francisco Sepulveda and Adrian M. Stoica},
  booktitle={International Conference on Intelligent User Interfaces},
  year={2013}
}
We explored the possibility of controlling a spacecraft simulator using an analogue Brain-Computer Interface (BCI) for 2-D pointer control. This is a difficult task, for which no previous attempt has been reported in the literature. Our system relies on an active display which produces event-related potentials (ERPs) in the user's brain. These are analysed in real-time to produce control vectors for the user interface. In tests, users of the simulator were told to pass as close as possible to… 

Figures and Tables from this paper

A collaborative Brain-Computer Interface to improve human performance in a visual search task

This paper uses a collaborative brain-computer interface to integrate the decision confidence of multiple non-communicating observers as a mechanism to improve group decisions and uses spatial CSP filters instead of the spatio-temporal PCA, resulting in a significant reduction in the number of features and free parameters used in the system.

Exploiting code-modulating, Visually-Evoked Potentials for fast and flexible control via Brain-Computer Interfaces

This dissertation presents the first use of a code-modulating, Visually-Evoked Potential (cVEP) for a navigation and control task and shows for the first time that the cVEP potentials is indeed very flexible without loosing much speed or reliability.

Past and Future of Multi-Mind Brain-Computer Interfaces

This chapter reviews the history of multi-mind BCIs that have their root in the hyperscanning technique; the collaborative and competitive approaches; and the different ways that exist to integrate the brain signals from multiple people and optimally form groups to maximize performance.

Collaborative Brain-Computer Interface for Aiding Decision-Making

Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule, corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making.

A Survey of Interactive Systems based on Brain- Computer Interfaces

Only noninvasive BCIs are addressed, since this kind of capture is the only one to not present risk to human health, and a discussion on challenges and future of this subject matter is discussed.

Competing and Collaborating Brains: Multi-brain Computer Interfacing

  • A. Nijholt
  • Computer Science
    Brain-Computer Interfaces
  • 2015
This chapter surveys the possibilities of brain-computer interface applications that assume two or more users, where at least one of the users’ brain activity is used as input to the application, and looks at BCI applications where more than one user is involved.

An era of brain-computer interface: BCI migration into space

Brain-computer interface can help astronauts deal with complicated tasks with a minimal mental workload, and it may provide intelligent communication systems, maximize safety and security, facilitate space discovery missions, and enhance astronauts' overall health and wellbeing.

Improved targeting through collaborative decision-making and brain computer interfaces

This paper explores, from a broad perspective, how the collaboration of a group of people can increase the performance on a simple target identification task, and analyzes the role of brain-computer interfaces in collaborative targeting.

Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces

A single-trial target-localisation collaborative Brain-Computer Interface (cBCI) is proposed that exploits this ERP to automatically approximate the horizontal position of targets in aerial images and suggests that BCIs for automated triaging can be improved by integrating two classification systems: one devoted to target detection and another to detect the attentional shifts associated with lateral targets.
...

References

SHOWING 1-10 OF 42 REFERENCES

Control of a humanoid robot by a noninvasive brain-computer interface in humans.

It is shown that by leveraging advances in robotics, an interface based on EEG can be used to command a partially autonomous humanoid robot to perform complex tasks such as walking to specific locations and picking up desired objects.

Prospects of brain-machine interfaces for space system control

A Collaborative Brain-Computer Interface for Improving Human Performance

  • Yijun WangT. Jung
  • Computer Science
    PloS one
  • 2011
Results suggest that a collaborative BCI can effectively fuse brain activities of a group of people to improve the overall performance of natural human behavior.

Toward a P300-based Computer Interface

This paper describes the initial research into the use of the P300 event related potential as a control signal in a computer interface for locked-in patients and develops a device which uses the occurrence of a P300 to control motion of a cursor on a computer screen.

Evolutionary Synthesis of a Trajectory Integrator for an Analogue Brain-Computer Interface Mouse

This paper attacks the difficult problem of integrating noisy and contradictory information provided at each time step by the signal processing systems into a coherent and precise trajectory for the mouse pointer using genetic programming, obtaining extremely promising results.

A hybrid brain interface for a humanoid robot assistant

A multi-functional hybrid brain-robot interface that provides a communication channel between humans and a state-of-the-art humanoid robot, Honda's Humanoid Research Robot, is developed.

Analogue mouse pointer control via an online steady state visual evoked potential (SSVEP) brain–computer interface

This paper introduces an online BCI in which control of a mouse pointer is directly proportional to a user's intent and performance is measured over a series of pointer movement tasks and compared to the traditional discrete output approach.

Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials.

Brain–computer interfaces for communication and control