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Graph Strength for Identification of Pre-training Desynchronization

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Intelligent Technologies: Design and Applications for Society (CITIS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 607))

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Abstract

Motor processing can result in coordinated changes of ongoing/decreasing brain neural activity or event-related de/synchronization (ERD/S) that raises brain responses over either contralateral brain hemisphere. Because of the affordability and time resolution provided, Electroencephalographic (EEG) signals are commonly used to acquire motor imagery paradigms. However, the widely-known condition of low-noise signals makes detection and spatial localization of ERD/S challenging. Here, to deal with the high variability between subjects, we propose to perform group analysis of graph representations extracted from the weighted Phase lock Index. Statistical thresholding of the functional connectivity estimates is also accomplished to improve the assessments of phase synchronization between electrodes. The obtained results on a real-world database with 50 individuals show that the proposed methodology improves interpretation of ERD/S, allowing better prediction of motor imagery ability in subjects having low skills for practicing this paradigm.

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Notes

  1. 1.

    http://gigadb.org/dataset/100295.

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Author information

Authors and Affiliations

  1. Signal Processing and Recognition Group, Universidad Nacional de Colombia, Manizales, Colombia

    Frank Yesid Zapata Castano, Andrés Marino Álvarez Meza & César Germán Castellanos Domínguez

  2. Instituto Superior Universitario Sucre, Quito, Ecuador

    Óscar Wladimir Gómez Morales

Authors
  1. Frank Yesid Zapata Castano
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  2. Óscar Wladimir Gómez Morales
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  3. Andrés Marino Álvarez Meza
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  4. César Germán Castellanos Domínguez
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Corresponding author

Correspondence to Óscar Wladimir Gómez Morales .

Editor information

Editors and Affiliations

  1. Campus El Vecino, Universidad Politécnica Salesiana, Cuenca, Ecuador

    Vladimir Robles-Bykbaev

  2. Research Centre on Production Management and Engineering - CIGIP, Universitat Politècnica de València, Alcoy, Spain

    Josefa Mula

  3. Rua Imaculada Conceiçao, Pontifícia Universidade Católica do Paraná – PUCPR, Curitiba, Brazil

    Gilberto Reynoso-Meza

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Zapata Castano, F.Y., Gómez Morales, Ó.W., Álvarez Meza, A.M., Castellanos Domínguez, C.G. (2023). Graph Strength for Identification of Pre-training Desynchronization. In: Robles-Bykbaev, V., Mula, J., Reynoso-Meza, G. (eds) Intelligent Technologies: Design and Applications for Society. CITIS 2022. Lecture Notes in Networks and Systems, vol 607. Springer, Cham. https://doi.org/10.1007/978-3-031-24327-1_4

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