EEG Representations of Spatial and Temporal Features in Imagined Speech and Overt Speech

Lee, Seo Hyun; Lee, Minji; Lee, Seong Whan

doi:10.1007/978-3-030-41299-9_30

Cited by 23 publications

(24 citation statements)

References 28 publications

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“…The experimental protocol followed the previous works [7], [20]. EEG data of nine subjects (three males; age 25.00 ± 2.96) performing imagined speech of thirteen words/phrases (ambulance, clock, hello, help me, light, pain, stop, thank you, toilet, TV, water, and yes) were analyzed.…”

Section: A Experimental Protocolsmentioning

confidence: 99%

Toward Imagined Speech based Smart Communication System: Potential Applications on Metaverse Conditions

Lee¹,

Lee²,

Lee³

2021

Preprint

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Recently, brain-computer interface (BCI) system is aiming to provide user-friendly and intuitive means of communication. Imagined speech has become an alternative neuroparadigm for communicative BCI since it relies directly on a person's speech production process, rather than using speechunrelated neural activity as the method of communication. Together with the current trends on BCI, we suggest a brainto-speech (BTS) system that operates by real-time decoding of multi-class imagined speech electroencephalography (EEG). Using the thirteen-class imagined speech data of nine subjects, we performed pseudo-online analysis in order to investigate the potential use of virtual BTS system in the real-world. Average accuracy of 46.54 ± 9.37 % (chance level = 7.7 %) and 75.56 ± 5.83 % (chance level = 50 %) was acquired in the thirteen-class and binary pseudo-online analysis, respectively. Together with the pseudo-online analysis of imagined speech decoding, we suggest possible form of future applications of imagined speech BCI as means of intuitive BCI communication. We provide potential applications on virtual smart home system and virtual assistant controlled by imagined speech. The virtual BTS system in this paper displays the possible form of real-world application and online training platform.

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Section: A Experimental Protocolsmentioning

confidence: 99%

Toward Imagined Speech based Smart Communication System: Potential Applications on Metaverse Conditions

Lee¹,

Lee²,

Lee³

2021

Preprint

Self Cite

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show abstract

“…The experimental protocol followed the previous works [16], [20]. Nine subjects (three males; age 25.00 ± 2.96) participated in the study.…”

Section: A Data Descriptionmentioning

confidence: 99%

“…Recent studies have shown some features and potentials of imagined speech decoding [16], [19], but fundamental neural properties and their practical use remain to be investigated. Therefore, research on the decoding of imagined speech requires the development of brain signal decoding techniques for more accurate and practical BCI [20], [21].…”

Section: Introductionmentioning

confidence: 99%

EEG-Transformer: Self-attention from Transformer Architecture for Decoding EEG of Imagined Speech

Lee¹,

Lee²

2021

Preprint

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Transformers are groundbreaking architectures that have changed a flow of deep learning, and many highperformance models are developing based on transformer architectures. Transformers implemented only with attention with encoder-decoder structure following seq2seq without using RNN, but had better performance than RNN. Herein, we investigate the decoding technique for electroencephalography (EEG) composed of self-attention module from transformer architecture during imagined speech and overt speech. We performed classification of nine subjects using convolutional neural network based on EEGNet that captures temporal-spectral-spatial features from EEG of imagined speech and overt speech. Furthermore, we applied the self-attention module to decoding EEG to improve the performance and lower the number of parameters. Our results demonstrate the possibility of decoding brain activities of imagined speech and overt speech using attention modules. Also, only single channel EEG or ear-EEG can be used to decode the imagined speech for practical BCIs.

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“…These endogenous paradigms are reported to be effective in BCI communication since they involve the user intention directly [1]. Attempts to robust decoding of the two paradigms with the investigation of their intrinsic features are being actively proposed [2]. However, the underlying features 20xx IEEE.…”

Section: Introductionmentioning

confidence: 99%

Functional Connectivity of Imagined Speech and Visual Imagery based on Spectral Dynamics

Lee

2021

2021 9th International Winter Conference on Brain-Computer Interface (BCI)

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Recent advances in brain-computer interface technology have shown the potential of imagined speech and visual imagery as a robust paradigm for intuitive brain-computer interface communication. However, the internal dynamics of the two paradigms along with their intrinsic features haven't been revealed. In this paper, we investigated the functional connectivity of the two paradigms, considering various frequency ranges. The dataset of sixteen subjects performing thirteen-class imagined speech and visual imagery were used for the analysis. The phase-locking value of imagined speech and visual imagery was analyzed in seven cortical regions with four frequency ranges. We compared the functional connectivity of imagined speech and visual imagery with the resting state to investigate the brain alterations during the imagery. The phase-locking value in the whole brain region exhibited a significant decrease during both imagined speech and visual imagery. Broca and Wernicke's area along with the auditory cortex mainly exhibited a significant decrease in the imagined speech, and the prefrontal cortex and the auditory cortex have shown a significant decrease in the visual imagery paradigm. Further investigation on the brain connectivity along with the decoding performance of the two paradigms may play a crucial role as a performance predictor.

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EEG Representations of Spatial and Temporal Features in Imagined Speech and Overt Speech

Cited by 23 publications

References 28 publications

Toward Imagined Speech based Smart Communication System: Potential Applications on Metaverse Conditions

Toward Imagined Speech based Smart Communication System: Potential Applications on Metaverse Conditions

EEG-Transformer: Self-attention from Transformer Architecture for Decoding EEG of Imagined Speech

Functional Connectivity of Imagined Speech and Visual Imagery based on Spectral Dynamics

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