A collection of chapters and abstracts from both 2017 and 2019 Neuroadaptive Technology conferences were published last week by Elsevier, edited by myself and Thorsten Zander. You can find full details about the content of the book directly from the Elsevier website here.
I’ve reproduced the preface from the collection below to give a sense of what the collection is about and how the book and the conferences came to be.
“Back in the late noughties, there was a period of intensified interest in the concept of a brain-computer interfaces (BCI). The idea of using real-time measures of brain activity to communicate directly with a computer was nothing new, but BCI research (at the time) was generally constrained to medical applications and clinical groups. The primary impetus for increased interest in the topic was the idea that people without clinical conditions could utilise BCIs, which stimulated enormous discussion about what kinds of applications were possible. There was a feeling back then that BCI research, which had been highly niche and specialised, was spilling over into the relative mainstream of human-computer interaction.
Those early conference sessions and workshops were dominated by research on active BCI, where neurophysiological signals represent active intentions and serve as a proxy for an input control device like a mouse or a joystick. We were in a minority during those early sessions because we were both working on system concepts where physiology was monitored implicitly, and the interface adapted with no requirement for active cognition on behalf of the user. One of us had developed the existing concept of physiological computing into a broad category of technology where systems adapted to implicit changes in neurophysiology and psychophysiology, united by the cybernetic concept of closed-loop control. The other had extended the concept of a BCI to include an approach called passive BCI, which implicitly monitored the user and allowed the system to develop context awareness.
When we talked, we discovered that we had at least two things in common, we were both interested in closed-loop control using signals from the brain and the body and we experienced a shared frustration that our work didn’t fit comfortably into existing conference forums. As we both regularly attended a range of meetings, we could see work on this topic of implicit monitoring being submitted and presented, but presentations often emphasised one specific aspect, such as sensors or signal processing aspects or machine learning, which depended on the specific focus of the conference. We both felt that the ‘passive’ approach was important enough to warrant its own scientific meeting where all aspects of the closed loop design were equally represented, from sensors to signal treatment through to interface design and evaluation of the user experience.