Evaluation of a proposal for sustained attention training through BCI with an estimate of effective connectivity

Casagrande, W. D.; Delisle-Rodríguez, Denis; Nakamura-Palacios, Ester Miyuki; Frizera-Neto, Anselmo

doi:10.1109/smc53654.2022.9945378

Cited by 1 publication

(1 citation statement)

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“…In addition, it has the advantage of not requiring the use of expensive or invasive BCI (Brain-Computer Interface) equipment, which makes it a viable and economical alternative for studies related to mathematical processing. This methodology is supported by previous scientific research that has established connections between brain activity and mental concentration while performing specific cognitive tasks (Goldin, 2022) (Casagrande et al, 2022) (Shafeeg et al, 2023). Therefore, this strategy could provide valuable information about how the brain of university students processes mathematics and how concentration levels vary during different stages of mathematical problem solving.…”

Section: Description Of the Problemmentioning

confidence: 80%

Exploration of the Relationship between Brain Signals and Concentration in Solving Mathematical Operations in University Students using Brain-Computer Interface

Marquez,

Magdaleno-Palencia,

Alanis

2023

JER

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The present study explores the relationship between brain signals and the level of concentration in solving mathematical operations by university students. Through the use of Brain-Computer Interface (BCI) technology, brain waves were recorded and analyzed during the execution of mathematical tasks of different levels of difficulty. The results indicate that there is a clear association between fluctuations in brain wave frequencies and focused attention, being more evident in the frontal regions of the brain. Furthermore, an artificial neural network was implemented to predict concentration levels based on the collected brain signals. These findings suggest that concentration plays a critical role in mathematical performance and support the idea that monitoring brain signals can provide valuable information about the cognitive processes involved in intellectually challenging tasks. In educational terms, these results have implications for the design of pedagogical strategies that promote self-regulation and sustained attention in mathematical learning, with the potential to improve academic achievement in this area.

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Section: Description Of the Problemmentioning

confidence: 80%