Towards improved BCI based on human learning principles

Abstract

Although EEG-based BCI are very promising for numerous applications, they mostly remain prototypes not used outside laboratories, due to their low reliability. Poor BCI performances are partly due to imperfect EEG signal processing algorithms but also to the user, who may not be able to produce reliable EEG patterns. This paper presents some of our current work that aims at addressing the latter, i.e., at guiding users to learn BCI control mastery. First, this paper identifies some theoretical (based on human learning psychology models) and practical limitations of current standard BCI training approaches and thus the need for alternative ones. To try to address these limitations, we conducted a study to explore what kind of users can use a BCI and why, and will present the main results. We also present new feedback types we designed to help users to learn BCI control skills more efficiently.

Brain-Computer Interface and Motor Imagery Training: The Role of Visual Feedback and Embodiment

“…Modulation of one's own brain signals is not an intuitive task, and therefore the user needs to practice and learn the BCI "skill." However, an efficient learning of a skill requires optimized training protocols that consider the user's psychological states (such as motivation, attention, confidence, and satisfaction) in order to ensure more effort and better performance from the user's side [44]. Kleih et al have shown that in the control of a P300 BCI, the level of P300 amplitude was significantly correlated with the level of self-rated motivation, that is, highly motivated subjects were able to communicate through BCI faster than less motivated subjects [45].…”

Heading for new shores! Overcoming pitfalls in BCI design

“…Is that really the best way we can train our users to gain BCI control? To answer that question, we have studied the literature from the fields of human learning, educational science and instructional design [11, 57]. These fields have indeed studied across multiple disciplines, e.g., language learning, motor learning or mathematical learning, what are the principles and guidelines that can ensure efficient and effective training approaches.…”

“…Note that an engaging environment does not necessarily have to be a visually appealing but complex and charged visual environment (like most modern video games), as it may overload the user. Unfortunately, there are many other training principles and guidelines not satisfied by classical BCI training [11, 57]. …”

Semiotic Training for Brain-Computer Interfaces

“…In case of BCI, the semiotic training will develop spatial abilities. This is important because according to the hypothesis [10]- [11] spatial abilities may efficiently contribute to the development of BCI skill.…”

“…Contemporary BCI is still barely used outside laboratories [10] [11] and thus does not allow to observe diversified and complex physical movements implemented by brain force. Therefore, it is productive to make preliminary observations concerning the abovementioned substantial features of human intentional imagination on the base of other data that are more easily acceptable and do not need sophisticated or expensive equipment.…”