Brainware: synergizing software systems and neural inputs
Author(s) -
Shihong Huang,
Emmanuelle Tognoli
Publication year - 2014
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2591062.2591131
Subject(s) - computer science , software , brain–computer interface , human–computer interaction , software system , artificial neural network , interface (matter) , artificial intelligence , software engineering , programming language , electroencephalography , psychology , bubble , psychiatry , maximum bubble pressure method , parallel computing
The rapid advances in the field of Brain Computer Interfaces (BCI) are expected to enrich the quality of people’s lives. BCI connects computer actions with neural inputs—signals indicating the user’s intentions, desired actions, attention, thoughts, memories, and emotions. BCI applications present significant challenges for computer science and software engineering research: an avalanche of neural signals will make their way as direct input into software systems. Given the differences between neural inputs and behavioral ones, the integration of neural inputs will require special approaches, and not simply adding yet more user interface channels to pre-existing software systems. This paper explores the challenges of designing and implementing self-adaptive software systems that could synergize brain states. After framing the problem, its rationale and possible solutions, in this paper we argue that the software engineering community ought to investigate how to incorporate neural inputs into software systems. The days are now upon us when software systems can “feel” and “anticipate” the users’ intentions and therefore react self-adaptively and synergistically to their needs.
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