EEG Control of a Virtual Helicopter in 3-Dimensional Space Using Intelligent Control Strategies

Abstract

Films like Firefox, Surrogates, and Avatar have explored the possibilities of using brain-computer interfaces (BCIs) to control machines and replacement bodies with only thought. Real world BCIs have made great progress toward that end. Invasive BCIs have enabled monkeys to fully explore 3-dimensional (3D) space using neuroprosthetics. However, non-invasive BCIs have not been able to demonstrate such mastery of 3D space. Here, we report our work, which demonstrates that human subjects can use a non-invasive BCI to fly a virtual helicopter to any point in a 3D world. Through use of intelligent control strategies, we have facilitated the realization of controlled flight in 3D space. We accomplished this through a reductionist approach that assigns subject-specific control signals to the crucial components of 3D flight. Subject control of the helicopter was comparable when using either the BCI or a keyboard. By using intelligent control strategies, the strengths of both the user and the BCI system were leveraged and accentuated. Intelligent control strategies in BCI systems such as those presented here may prove to be the foundation for complex BCIs capable of doing more than we ever imagined.

Performance of Motor Imagery Brain-Computer Interface Based on Anodal Transcranial Direct Current Stimulation Modulation

“…In the past few years, many lines of research focused on developing sophisticated pattern recognition and classification algorithms to decode reliable BCI control signal from noisy brain activity [7], [8], but the complexity of the algorithm challenged its applicability in real time. From the user side, although making trained feedback adapt to a BCI system is common [9]- [12], repetitive training increases fatigue and is not effective for all users. Hence, there is a growing interest to find out whether other techniques, such as neuro-modulation approaches, could promote the user ability to achieve an improved EEG BCI classification accuracy in a relatively short time.…”

Towards Brain Computer Interfaces for Recreational Activities: Piloting a Drone

“…One particular continuous control application for BCIs of interest for this article is 3D navigation for the purpose of piloting a drone. Royer et al [19] first evaluate the feasibility of the 2D control of an helicopter in a virtual environment, followed by Doud et al for 3D control [20] with the motivation of achieving a means for telepresence. Finally LaFleur et al [4] apply this technique for the 3D control of a real AR.Drone, with good success by using an Operant Conditioning training for 2 months on 5 users.…”

Brainware: synergizing software systems and neural inputs

“…This type of BCI resorted to selective attention to identify which letter displayed on a screen a person was attentive to. A number of applications also examined how to control a cursor or an object on the screen using brain activity [31][2] or objects placed in the environment [21]. Interest also arose for signals encoding the brain's emotional states through the development of effective BCIs [20].…”