Collaborative Brain-Computer Interface for people with severe motor disabilities: From Yueqing Li’s dissertation (2014)
Brain-computer interfaces (BCIs) are new technologies that allow users to communicate with the outside world or control external equipment without the use of “normal” pathways of peripheral nerves and muscles. For people with motor disabilities, BCIs provide a degree of communication and control that can help make simple tasks more convenient and ultimately reduce the burden placed on caregivers at times. Meanwhile, BCIs could also be used to study brain structure and function in the context of human cognition and behavior. SSVEP BCIs are non-invasive BCIs that use SSVEP brain signals to communicate or control. Without initial training needed, users can use SSVEP BCIs by only focusing on visual stimuli.
However, current efforts in the area of BCI technology still present significant gaps. Most existing BCIs serve only single users. Few studies have explored the integration of BCIs in “normal” life, especially to support interactive work and collaboration with other people. There is a general lack of understanding regarding how BCIs should support collaborative work between users with motor disabilities and between users with and without motor disabilities under various task conditions.
The objective of this research was to investigate the collaborative behavior of people with motor disabilities (i.e., amyotrophic lateral sclerosis, ALS) using a collaborative BCI system that utilizes steady-state visually evoked potentials (SSVEPs). The NC State Brainbot BCI was used as a testbed for the research.
The research described in this paper derived from two separate studies. Study 1 was a fundamental investigation of SSVEPs in which user sensitivity to specific visual stimuli was assessed through the manipulation of LED light frequency and color.
The study employed three types of dependent variables: (a) task performance (response rate), (b) brain activity (spectral power) and (c) user evaluations (subjective ratings of fatigue and preference toward light frequency and color). Study 2 recruited the same group of participants as Study 1 and examined the effects of the collaboration modes under user-specific stimuli configurations determined in Study 1.
Besides an individual mode where a single user performs a task, two collaboration modes were presented: (a) Sequential mode: a pair of users take turns to perform a task, (b) Simultaneous mode: a pair of users perform a task at the same time (i.e., brain signals from both users are used to control the BCI). Moreover, the effect of luminance contrast was investigated to validate the applicability of the SSVEP-based BCI. Study 2 employed three types of dependent measures, including: (a) task performance (accuracy, task completion time, and information transfer rate (ITR)), (b) brain activity (spectral power), and (c) user subjective evaluations. Participants with motor disabilities were recruited from the ALS Association and the local community. Age-matched able-bodied participants were recruited from the local community to investigate the effect of motor disability on C-BCI performance.
The research was expected to yield fundamental knowledge of BCI-supported cooperative work, an understanding of the support needed for interaction with BCIs for group activities, as well as design considerations for collaborative BCIs. Meanwhile, the SSVEP BCI paradigm can be used as a testbed to investigate the important topics in human factors/ergonomics, such as situation awareness, teamwork, and decision making.