Exploring methodological frameworks for a mental task-based near-infrared spectroscopy brain–computer interface

Weyand, Sabine; Takehara‐Nishiuchi, Kaori; Chau, Tom

doi:10.1016/j.jneumeth.2015.07.007

Cited by 11 publications

(18 citation statements)

References 54 publications

(92 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Had task choice been exclusively based on performance, a change in accuracy may have been more apparent. 42 However, our findings collectively suggest that perceived ease-of-use may trump accuracy for some users and may facilitate BCI control. For example, the benefits of personalization in initial acquisition and learning have been demonstrated in other areas of research.…”

Section: Online and Offline Classificationmentioning

confidence: 69%

Section: Motivation For User-selected Personalized Mental Tasksmentioning

confidence: 86%

“…42 We showed that user-selected personalized tasks have the potential to yield higher perceived ease-of-use ratings. 42 However, further studies are needed to verify the value of personalized tasks by comparing personalized and prescribed task selection schemes, particularly in an online paradigm. To the best of our knowledge, no other NIRS-BCI study has explored the use of personalized tasks and no other BCI studies have allowed users to choose personalized tasks based on both performance and ease-of-use.…”

Section: Motivation For User-selected Personalized Mental Tasksmentioning

confidence: 86%

“…This finding corroborates that of our previous offline single-group study, where no significant difference was observed between the accuracies of user-selected personalized mental tasks and prescribed tasks. 42 This study adds to the expanding literature of online NIRS-BCI research. Online classification is a critical step toward realworld BCI applications and presents various challenges not applicable to offline classification, including hardware and software adaptations to allow for immediate classification, and to address classifier generalization issues.…”

Section: Online and Offline Classificationmentioning

confidence: 90%

“…Incidentally, our previous offline single-group study also identified a significantly greater perceived ease-of-use for userselected personalized mental tasks compared to prescribed tasks. 42 The significance of developing an easier to use BCI has been well established in literature. As described in Sec.…”

Section: Ease-of-usementioning

confidence: 99%

See 4 more Smart Citations

Usability and performance-informed selection of personalized mental tasks for an online near-infrared spectroscopy brain-computer interface

et al. 2015

Self Cite

View full text Add to dashboard Cite

Abstract. Brain-computer interfaces (BCIs) allow individuals to use only cognitive activities to interact with their environment. The widespread use of BCIs is limited, due in part to their lack of user-friendliness. The main goal of this work was to develop a more user-centered BCI and determine if: (1) individuals can acquire control of an online near-infrared spectroscopy BCI via usability and performance-informed selection of mental tasks without compromising classification accuracy and (2) the combination of usability and performance-informed selection of mental tasks yields subjective ease-of-use ratings that exceed those attainable with prescribed mental tasks. Twenty able-bodied participants were recruited. Half of the participants served as a control group, using the state-of-the-art prescribed mental strategies. The other half of the participants comprised the study group, choosing their own personalized mental strategies out of eleven possible tasks. It was concluded that users were, in fact, able to acquire control of the more user-centered BCI without a significant change in accuracy compared to the prescribed task BCI. Furthermore, the personalized BCI yielded higher subjective ease-of-use ratings than the prescribed BCI. Average online accuracies of 77 AE 12.9% and 73 AE 12.9% were achieved by the personalized and prescribed mental task groups, respectively.

show abstract

Section: Online and Offline Classificationmentioning

confidence: 69%

Section: Motivation For User-selected Personalized Mental Tasksmentioning

confidence: 86%