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The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications

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Abstract

The investigation of innovative Human-Computer Interfaces (HCI) provides a challenge for future multimedia research and development. Brain-Computer Interfaces (BCI) exploit the ability of human communication and control bypassing the classical neuromuscular communication channels. In general, BCIs offer a possibility of communication for people with severe neuromuscular disorders, such as Amyotrophic Lateral Sclerosis (ALS) or spinal cord injury. Beyond medical applications, a BCI conjunction with exciting multimedia applications, e.g., a dexterity game, could define a new level of control possibilities also for healthy customers decoding information directly from the user’s brain, as reflected in electroencephalographic (EEG) signals which are recorded non-invasively from user’s scalp. This contribution introduces the Berlin Brain–Computer Interface (BBCI) and presents setups where the user is provided with intuitive control strategies in plausible gaming applications that use biofeedback. Yet at its beginning, BBCI thus adds a new dimension in multimedia research by offering the user an additional and independent communication channel based on brain activity only. First successful experiments already yielded inspiring proofs-of-concept. A diversity of multimedia application models, say computer games, and their specific intuitive control strategies, as well as various Virtual Reality (VR) scenarios are now open for BCI research aiming at a further speed up of user adaptation and increase of learning success and transfer bit rates.

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Correspondence to Roman Krepki.

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Manuscript received on November the 25th, 2003. This work was supported by a grant of the Bundesministerium für Bildung und Forschung (BMBF), FKZ 01IBB02A and 01IBB02B.

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Krepki, R., Blankertz, B., Curio, G. et al. The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications. Multimed Tools Appl 33, 73–90 (2007). https://doi.org/10.1007/s11042-006-0094-3

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