Abstract
We usually look at an object when we are going to manipulate it. Thus, eye tracking can be used to communicate intended actions. An effective human-machine interface, however, should be able to differentiate intentional and spontaneous eye movements. We report an electroencephalogram (EEG) marker that differentiates gaze fixations used for control from spontaneous fixations involved in visual exploration. Eight healthy participants played a game with their eye movements only. Their gaze-synchronized EEG data (fixation-related potentials, FRPs) were collected during game's control-on and control-off conditions. A slow negative wave with a maximum in the parietooccipital region was present in each participant's averaged FRPs in the control-on conditions and was absent or had much lower amplitude in the control-off condition. This wave was similar but not identical to stimulus-preceding negativity, a slow negative wave that can be observed during feedback expectation. Classification of intentional vs. spontaneous fixations was based on amplitude features from 13 EEG channels using 300 ms length segments free from electrooculogram contamination (200–500 ms relative to the fixation onset). For the first fixations in the fixation triplets required to make moves in the game, classified against control-off data, a committee of greedy classifiers provided 0.90 ± 0.07 specificity and 0.38 ± 0.14 sensitivity. Similar (slightly lower) results were obtained for the shrinkage Linear Discriminate Analysis (LDA) classifier. The second and third fixations in the triplets were classified at lower rate. We expect that, with improved feature sets and classifiers, a hybrid dwell-based Eye-Brain-Computer Interface (EBCI) can be built using the FRP difference between the intended and spontaneous fixations. If this direction of BCI development will be successful, such a multimodal interface may improve the fluency of interaction and can possibly become the basis for a new input device for paralyzed and healthy users, the EBCI “Wish Mouse.”
Highlights
A brain-computer interface (BCI) is a tool of control and communication without using muscles or peripheral nerves, through the use of brain signals only (Wolpaw et al, 2002)
For demonstrating the possibility of developing an Eye-Brain-Computer Interface (EBCI) it was more important to prove that we obtained an EEG marker that was free from EOG contamination
This study demonstrated that intentional gaze fixations for 500 ms, used to control a computer interface through eye tracking technology, can be discriminated from spontaneous gaze fixations of the same duration using only 300 ms EEG segments
Summary
A brain-computer interface (BCI) is a tool of control and communication without using muscles or peripheral nerves, through the use of brain signals only (Wolpaw et al, 2002). A typical BCI does not recognize the user’s whishes or action plans directly; to send a command, a user needs to execute one of a limited range of motor imagery, cognitive or perceptual tasks that can evoke recognizable brain signals. Such tasks are typically unrelated to the current activity and their use imposes additional mental load and decreases the fluency of BCI use. Invasive BCIs are promising, but high risks and costs associated with brain surgery require further efforts to make this technology acceptable even for severely paralyzed patients (Lahr et al, 2015; Bowsher et al, 2016; Waldert, 2016)
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