{"type":"ScholarlyArticle","title":"A Hierarchical Architecture for Adaptive Brain-Computer Interfacing","authors":[{"name":"Mike Chung","slug":"mike-chung","given":"Mike","family":"Chung","affiliation":""},{"name":"Willy Cheung","slug":"willy-cheung","given":"Willy","family":"Cheung","affiliation":""},{"name":"Reinhold Scherer","slug":"reinhold-scherer","given":"Reinhold","family":"Scherer","affiliation":""},{"name":"Rajesh P. N. Rao","slug":"rajesh-p-n-rao","given":"Rajesh P. N.","family":"Rao","affiliation":""}],"abstract":"Brain-computer interfaces (BCIs) allow a user to directly control devices such as cursors and robots using brain signals. Non-invasive BCIs, e.g., those based on electroencephalographic (EEG) signals recorded from the scalp, suffer from low signal-to-noise ratio which limits the bandwidth of control. Invasive BCIs allow fine-grained control but can leave users exhausted since control is typically exerted on a moment-by-moment basis. In this paper, we address these problems by proposing a new adaptive hierarchical architecture for brain-computer interfacing. The approach allows a user to teach the BCI new skills on-the-fly; these learned skills are later invoked directly as high-level commands, relieving the user of tedious low-level control. We report results from four subjects who used a hierarchical EEG-based BCI to successfully train and control a humanoid robot in a virtual home environment. Gaussian processes were used for learning high-level commands, allowing a BCI to switch between autonomous and user-guided modes based on the current estimate of uncertainty. We also report the first instance of multi-tasking in a BCI, involving simultaneous control of two different devices by a single user. Our results suggest that hierarchical BCIs can provide a flexible and robust way of controlling complex robotic devices in real-world environments.","doi":"10.5591/978-1-57735-516-8/IJCAI11-277","url":"https://ijcai.org/proceedings/2011/277","pdf":"https://ijcai.org/proceedings/2011/0277.pdf","markdown":"https://ijcai.org/proceedings/2011/277.md","bibtex":"https://ijcai.org/proceedings/2011/bibtex/277","volume":{"slug":"2011","title":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2011","url":"https://ijcai.org/proceedings/2011/","year":2011,"location":"Barcelona, Catalonia, Spain","dates":"16–22 July 2011","editors":"Toby Walsh","isbn":"978-1-57735-512-0; 978-1-57735-513-7; 978-1-57735-514-4; 978-1-57735-515-1; 978-1-57735-516-8","publisher":"AAAI Press/International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":277,"pages":{"first":1647,"last":1651},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}