2019 IEEE International Conference on Data Mining (ICDM) 2019
DOI: 10.1109/icdm.2019.00189
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Learning Attentional Temporal Cues of Brainwaves with Spatial Embedding for Motion Intent Detection

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Cited by 8 publications
(1 citation statement)
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“…The manual approach is limited by inherent knowledge and expertise, resulting in suboptimal performance and time-consuming model development. Moreover, EEG signals exhibit substantial variability among subjects due to the difference in individual physiological behaviours [13]. This variability necessitates the development of user-specific models to ensure effectiveness for each subject, further increasing the labour and time costs associated with the model development process.…”
Section: Introductionmentioning
confidence: 99%
“…The manual approach is limited by inherent knowledge and expertise, resulting in suboptimal performance and time-consuming model development. Moreover, EEG signals exhibit substantial variability among subjects due to the difference in individual physiological behaviours [13]. This variability necessitates the development of user-specific models to ensure effectiveness for each subject, further increasing the labour and time costs associated with the model development process.…”
Section: Introductionmentioning
confidence: 99%