Logo

Dr. Vangelis P. Oikonomou -
Publications

Journals

  1. M. Grammatikopoulou, I. Lazarou, V. Alepopoulos, L. Mpaltadoros, V. P. Oikonomou, T. G. Stavropoulos, S. Nikolopoulos, I. Kompatsiaris, M. Tsolaki, "Assessing the cognitive decline of people in the spectrum of AD by monitoring their activities of daily living in an IoT-enabled smart home environment: a cross-sectional pilot study.", Frontiers in Aging Neuroscience. 16:1375131, March 2024. https://doi.org/10.3389/fnagi.2024.1375131
  2. K. Georgiadis, F. P. Kalaganis, K. Riskos, E. Matta, V. P. Oikonomou, I. Yfantidou, D. Chantziaras, K. Pantouvakis, S. Nikolopolos, N. A. Laskaris, I. Kompatsiaris, "NeuMa - the absolute Neuromarketing dataset en route to an holistic understanding of consumer behaviour.", Sci Data 10, 508 (2023). https://doi.org/10.1038/s41597-023-02392-9
  3. I. Lazarou, V. P. Oikonomou, L. Mpaltadoros, M. Grammatikopoulou, V. Alepopoulos, T. G. Stavropoulos, A. Bezerianos, S. Nikolopoulos, I. Kompatsiaris, M. Tsolaki and RADAR-AD Consortium, "Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study.", Front. Aging Neurosci. 15:1167410. doi: 10.3389/fnagi.2023.1167410
  4. V. P. Oikonomou, K. Georgiadis, F. Kalaganis, S. Nikolopoulos, I. Kompatsiaris, "A Sparse Representation Classification Scheme for the Recognition of Affective and Cognitive Brain Processes in Neuromarketing.", Sensors. 2023; 23(5):2480. https://doi.org/10.3390/s23052480
  5. F. Kalaganis, N. Laskaris, V. Oikonomou, S. Nikopolopoulos, I. Kompatsiaris, "Revisiting Riemannian geometry-based EEG decoding through approximate joint diagonalization.", Journal on Neural Engineering, vol. 19, no. 6, December 2022. https://iopscience.iop.org/article/10.1088/1741-2552/aca4fc
  6. I. Lazarou, K. Georgiadis, S. Nikolopoulos, V. P. Oikonomou, T. Stavropoulos, A. Tsolaki, I. Kompatsiaris, M. Tsolaki, and the RADAR-AD Consortium, "Exploring Network Properties Across Preclinical Stages of Alzheimer's Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study.", Journal of Alzheimers Disease, 87(2), May 2022. https://content.iospress.com/articles/journal-of-alzheimers-disease/jad215421
  7. K. Georgiadis, F. Kalaganis, V. Oikonomou, S. Nikolopoulos, N. Laskaris, I. Kompatsiaris, "RNeuMark: A Riemannian EEG Analysis Framework for Neuromarketing.", Brain Inf. 9, 22 (2022). https://doi.org/10.1186/s40708-022-00171-7
  8. I. Lazarou, S. Nikolopoulos, K. Georgiadis, V. Oikonomou, A. Mariakaki, I. Kompatsiaris, "Exploring the Connection of Brain Computer Interfaces and Multimedia Use With the Social Integration of People With Various Motor Disabilities: A Questionnaire-Based Usability Study.", Front Digit Health. 2022 Aug 4;4:846963. doi: 10.3389/fdgth.2022.846963
  9. I. Lazarou, K. Georgiadis, S. Nikolopoulos, V. Oikonomou, T. Stavropoulos, A. Tsolaki, I. Kompatsiaris, M. Tsolaki and the RADAR-AD Consortium, "Exploring network properties across preclinical stages of Alzheimer’s Disease using a visual short-term memory and attention task with high-density EEG: A brain-connectome neurophysiological study", Journal of Alzheimer’s Disease, Feb 2022;87(2):643-664. doi: 10.3233/JAD-215421.
  10. F. Kalaganis, K. Georgiadis, V. Oikonomou, N. Laskaris, S. Nikolopoulos, I. Kompatsiaris, "Unlocking the Subconscious Consumer Bias: A Survey on the Past, Present, and Future of Hybrid EEG Schemes in Neuromarketing.", Frontiers in Neuroergonomics. 2021. Vol. 2. doi: 10.3389/fnrgo.2021.672982
  11. I. Lazarou, K. Georgiadis, S. Nikolopoulos, V. Oikonomou, A. Tsolaki, I. Kompatsiaris, M. Tsolaki, D. Kugiumtzis, "A Novel Connectome-Based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer’s Disease by Using Resting-State High-Density", EEG EGI GES 300. Brain Sci. 2020, 10 (6), 392.
  12. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures", in IEEE Access, vol. 8, pp. 98572-98583, 2020, doi: 10.1109/ACCESS.2020.2997116.
  13. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "A Bayesian Multiple Kernel Learning Algorithm for SSVEP BCI Detection", in IEEE Journal of Biomedical and Health Informatics, vol. 23, no. 5, pp. 1990-2001, Sept. 2019. DOI: 10.1109/JBHI.2018.2878048
  14. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "A Bayesian Multiple Kernel Learning Algorithm for SSVEP BCI detection", IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2018.2878048
  15. S. Nikolopoulos, P. Petrantonakis, K. Georgiadis, F. Kalaganis, G. Liaros, I. Lazarou, K. Adam, A. Papazoglou-Chalikias, E. Chatzilari, V. Oikonomou, C. Kumar, R. Menges, S. Staab, D. Müller, K. Sengupta, S. Bostantjopoulou, Z. Katsarou, G. Zeilig, M. Plotnik, A. Gotlieb, S. Fountoukidou, J. Ham, D. Athanasiou, A. Mariakaki, D. Comandicci, E. Sabatini, W. Nistico, M. Plank, I. Kompatsiaris, "A multimodal dataset for authoring and editing multimedia content: The MAMEM project", Data in Brief, 3 November 2017, ISSN 2352-3409, DOI: 10.1016/j.dib.2017.10.072.
  16. V. Oikonomou, G. Liaros, K. Georgiadis, E. Chatzilari, K. Adam, S. Nikolopoulos, I. Kompatsiaris, "Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs", Technical Report - eprint arXiv:1602.00904, February 2016

Conference

  1. V. Oikonomou, K. Geordiadis, F. Kalaganis, S. Nikolopoulos, I. Kompatsiaris, "Prediction of Successful Memory Formation during Audiovisual advertising using EEG signals.", In IEEE Conference on Artificial Intelligence (CAI), Singapore, 2024 pp. 1111-1116. DOI: 10.1109/CAI59869.2024.00200
  2. F. P. Kalaganis, K. Georgiadis, V. P. Oikonomou, S. Nikolopoulos, N. A. Laskaris, I. Kompatsiaris, "Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding.", In: Liu, F., Zhang, Y., Kuai, H., Stephen, E.P., Wang, H. (eds) Brain Informatics. BI 2023. Lecture Notes in Computer Science(), vol 13974. Springer, Cham. https://doi.org/10.1007/978-3-031-43075-6_35
  3. K. Georgiadis, F. P. Kalaganis, V. P. Oikonomou, S. Nikolopoulos, N. A. Laskaris, I. Kompatsiaris, "Harneshing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry.", In: Liu, F., Zhang, Y., Kuai, H., Stephen, E.P., Wang, H. (eds) Brain Informatics. BI 2023. Lecture Notes in Computer Science(), vol 13974. Springer, Cham. https://doi.org/10.1007/978-3-031-43075-6_3
  4. V. Alepopoulos, M. Grammatikopoulou, I. Lazarou, L. Mpaltadoros, S. Nikolopoulos, V. P. Oikonomou, T. G. Stavropoulos, M. Tsolaki, I. Kompatsiaris and the RADAR-AD Consortium., "First insights exploring Activities of Daily Living performance captured through activity sensors in a Smart Home Environment as an indicator of cognitive decline: A cross-sectional Analysis.", In Alzheimer's Association International Conference, AAIC, 2023, Amsterdam, Netherlands, July 16-20, 2023, Volume 19, Issue S15 Supplement: Biomarkers - Part2, e071138. https://alz.confex.com/alz/2023/meetingapp.cgi/Paper/71138
  5. I. Lazarou, V. Oikonomou, L. Mpaltadoros, M. Grammatikopoulou, V. Alepopoulos, S. Nikolopoulos, T. Stavropoulos, I. Kompatsiaris, M. Tsolaki and the RADAR-AD Consortium, "Investigating Brain Response of People with Cognitive Impairment during Meditation with wireless Muse EEG in a Smart-Home Setting.",13th Panhellenic Conference Of Alzheimer’s Disease (Picad) And 5th Mediterranean Conference On Neurodegenerative Diseases (Mecond). 9 - 12 February 2023, Thessaloniki, Greece.
  6. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "A Multitask Bayesian Framework for the analysis of Motor Imagery EEG Data.", 30th European Signal Processing Conference (EUSIPCO), 2022, pp. 1308-1312. DOI: 10.23919/EUSIPCO55093.2022.9909921
  7. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "A Novel Regression-based Algorithm for the recognition of SSVEP responses", 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE), 2020, pp. 519-522, doi: 10.1109/BIBE50027.2020.00090.
  8. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "A Novel Compressive Sensing Scheme under the Variational Bayesian Framework", 2019 27th European Signal Processing Conference (EUSIPCO), 2019, pp. 1-5, doi: 10.23919/EUSIPCO.2019.8902704.
  9. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "Discrimination of SSVEP responses using a kernel based approach", 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 762-766. DOI: 10.1109/EMBC.2019.8857685
  10. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "Sparse Graph-based Representations of SSVEP Responses Under the Variational Bayesian Framework", 2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE), Kragujevac, Serbia, 2021, pp. 1-6, doi: 10.1109/BIBE52308.2021.9635427
  11. F. Kalaganis, M. Seet, K. Georgiadis, V. Oikonomou, N. Laskaris, S. Nikolopoulos, I. Kompatsiaris, M. Panou, A. Dragomir, A. Bezerianos, "Reconstructing EOG From EEG Timeseries: A Spatial Filtering Approach.", In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 395-398. IEEE, 2021. doi:. PMID: 34891317. 10.1109/EMBC46164.2021.9630320
  12. I. Lazarou, K. Georgiadis, S. Nikolopoulos, V. Oikonomou, I. Kompatsiaris, M. Tsolaki, "Comparative study of people with Subjective cognitive Decline using high-density electroencephalograph combined with eye-tracker during selective and sustained attention memory test using visual stimuli", Virtual - 12th Panhellenic Conference of Alzheimer's Disease (PICAD) and the 4th Mediterranean Conference on Neurodegenerative Diseases (MeCoND), Thessaloniki Greece 18-21 February 2021
  13. V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "Motor Imagery Classification via Clustered-Group Sparse Representation", 19th IEEE International Conference on Bioinformatics and Bioengineering (BIBE), October 28-30, 2019, Athens, Greece
  14. V. Oikonomou, I. Kompatsiaris, "Sparse EEG Source Localization Under the Variational Bayesian Framework", 19th IEEE International Conference on Bioinformatics and Bioengineering (BIBE), October 28-30, 2019, Athens, Greece
  15. V. Oikonomou, S. Nikolopoulos, P. Petrantonakis, I. Kompatsiaris, "Sparse Kernel Machines for motor imagery EEG classification", Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’18) at the Honolulu, HI, USA, on July 17-21, 2018
  16. V. Oikonomou, G. Liaros, S. Nikolopoulos, I. Kompatsiaris, "Sparse Bayesian Learning for Multiclass Classification with application to SSVEP- BCI", 7th Graz Brain-Computer Interface Conference, September 18th – 22nd, 2017, Graz, Austria
  17. V. Oikonomou, K. Georgiadis, G. Liaros, S. Nikolopoulos, I. Kompatsiaris, "A comparison study on EEG signal processing techniques using motor imagery EEG data", 30th IEEE International Symposium on Computer-based Medical Systems, Special Track on Multimodal Interfaces for Natural Human Computer Interaction: Theory and Applications, IEEE CBMS 2017, June 22-24, 2017 Thessaloniki - Greece
  18. V. Oikonomou, A. Maronidis, G. Liaros, S. Nikolopoulos, I. Kompatsiaris, "Sparse Bayesian Learning for Subject Independent Classification with Application to SSVEP-BCI", Proceedings of the 8th International IEEE EMBS Conference on Neural Engineering, May 25-28, 2017, Shanghai China
  19. A. Maronidis, V. Oikonomou, S. Nikolopoulos, I. Kompatsiaris, "Steady State Visual Evoked Potential Detection Using Subclass Marginal Fisher Analysis", Proceedings of the 8th International IEEE EMBS Conference on Neural Engineering, May 25-28, 2017, Shanghai China

Books Chapters

  1. S. Nikolopoulos, K. Georgiadis, F. Kalaganis, G. Liaros, I. Lazarou, K. Adam, A. Papazoglou-Chalikias, E. Chatzilari, V. Oikonomou, P. Petrantonakis, I. Kompatsiaris, C. Kumar, R. Menges, S. Staab, D. Müller, K. Sengupta, S. Bostantjopoulou, Z. Katsarou, G. Zeilig, M. Plotnik, A. Gottlieb, S. Fountoukidou, J. Ham, D. Athanasiou, A. Mariakaki, D. Comanducci, E. Sabatini, W. Nistico, M. Plank, "The MAMEM Project - A dataset for multimodal human-computer interaction using biosignals and eye tracking information", (2017, July 24) Zenodo. DOI: 10.5281/zenodo.834154
Skip to content