Kunjira Kingphai

Search results

• 2024

  Mental workload assessment using deep learning models from EEG Signals: a systematic review

  Kingphai, K. & Moshfeghi, Y., 16 Aug 2024, (Accepted/In press) In: IEEE Transactions on Cognitive and Developmental Systems.

  Research output: Contribution to journal › Review article › peer-review

• On channel selection for EEG-based mental workload classification

  Kingphai, K. & Moshfeghi, Y., 15 Feb 2024, Machine Learning, Optimization, and Data Science: 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part II. Nicosia, G., Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P. M. & Umeton, R. (eds.). Cham: Springer-Verlag, p. 403-417 15 p. (Lecture Notes in Computer Science; vol. 14506).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Electroencephalogram 100%
  • Gated Recurrent Unit 45%
  • Riemannian Geometry 28%
  • Brain-Computer Interface 25%
  • Exist Number 14%
  1 Citation (Scopus)
• 2023

  On time series cross-validation for deep learning classification model of mental workload levels based on EEG signals

  Kingphai, K. & Moshfeghi, Y., 10 Mar 2023, Machine Learning, Optimization, and Data Science - 8th International Conference, LOD 2022, Revised Selected Papers. Nicosia, G., Giuffrida, G., Ojha, V., La Malfa, E., La Malfa, G., Pardalos, P., Di Fatta, G. & Umeton, R. (eds.). Cham, Switzerland: Springer Science and Business Media Deutschland GmbH, Vol. 13811. p. 402-416 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13811 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Deep Learning 100%
  • Workload 100%
  • Validation 100%
  • Classification Models 100%
  • Cross-Validation 100%
  7 Citations (Scopus)

  28 Downloads (Pure)
• 2021

  On EEG preprocessing role in deep learning effectiveness for mental workload classification

  Kingphai, K. & Moshfeghi, Y., 23 Nov 2021, Human Mental Workload: Models and Applications - 5th International Symposium, H-WORKLOAD 2021, Proceedings. Longo, L. & Leva, M. C. (eds.). Cham, Switzerland: Springer Science and Business Media Deutschland GmbH, p. 81-98 18 p. (Communications in Computer and Information Science; vol. 1493 CCIS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

  • Classification 100%
  • Deep Learning Model 100%
  • Preprocessing 100%
  • Workload 100%
  • Roles 100%
  11 Citations (Scopus)

• Mental workload prediction level from EEG signals using deep learning models

  Kingphai, K. & Moshfeghi, Y., 16 Sept 2021. 3 p.

  Research output: Contribution to conference › Paper › peer-review

  Open Access

  File

  • Deep Learning Model 100%
  • Gated Recurrent Unit 50%
  • Long Short-Term Memory Network 50%
  • Algorithms 16%
  • Bidirectional Long Short-Term Memory Network 16%
  7 Downloads (Pure)