Ear-EEG, Brain Computer Interface, Ear-EEG for sleep, microsleep, fatigue

See below for our recent contributions in this field.

Legend: MATLAB code, PDF files, Supplements and data.

    We have the following best paper/poster awards in this area:

  1. Eric Laithwaite Best Research Poster Prize (with Dr Valentin Goverdovsky) for the " Multimodal Biosensing Electrode", EEE Department, Imperial College London, 2014.
  2. Eric Laithwaite Best Research Poster Prize (with Dr David Looney) for the "Ear-EEG concept", EEE Department, Imperial College London, 2012.
  3. Best Student Paper Award, International Neural Network Society, for Ling Li et al., ``Modelling of Brain Consciousness Based on Collaborative Adaptive Filters'', 2010
  4. Best Paper Award for T. Rutkowski, T. Tanaka, A. Cichocki, D. Erickson, and D. P. Mandic, ``Interactive Component Extraction for Affective Brain Machine Interfaces'', ICIC 2019.
  5. Best Poster Award} for M. Golz, D. Sommer, and D. P. Mandic, ``Establishing Gold Standard for Microsleep Detection in Car Drivers'', in Monitoring Sleep and Sleepiness (MSSP), 2006.
  6. Best Student Paper Award, for K. Powels et al. ``Towards Mode Detection in Sleep Stages", RASC, 2002.

  7. Our research papers in this area
  8. D. Looney, V. Goverdovsky, I. Rosenzweig, M. J. Morrell, and D. P. Mandic, "A Wearable In-Ear Encephalography Sensor for Monitoring Sleep: Preliminary Observations from Nap Studies" Annals of the Americal Thoracic Society, September, 2016. [pdf]
  9. W. von Rosenberg, T. Chanwimalueang, V. Goverdovsky, D. Looney, D. Sharp, and D. P. Mandic "Smart helmet: Wearable multichannel ECG & EEG" IEEE Journal of Translational Engineering in Health and Medicine, accepted, 2016.
  10. Y. Tonoyan, D. Looney, D. P. Mandic, and M. M. van Hulle, "Discriminating multiple emotional states from EEG using a data-adaptive, multiscale information-theoretic approach" International Journal of Neural Systems, September, vol. 26, no. 2, pp. 1-16, 2016. [pdf]
  11. V. Goverdovsky, D. Looney, P. Kidmose, and D. P. Mandic, "In-ear EEG from viscoelastic generic earpieces: Robust and unobtrusive 24/7 monitoring" IEEE Sensors Journal, September, vol. 16, no. 1, pp. 271-277, 2016. [pdf]
  12. W. von Rosenberg, T. Chanwimalueang, V. Goverdovsky, and D. P. Mandic, "Smart helmet: Monitoring brain, cardiac and respiratory activity" Proc. 37th IEEE Annual Conference of the Engineering in Medicine and Biology Society (EMBC), pp. 1829-1832, 2015. [pdf]
  13. W. von Rosenberg, T. Chanwimalueang, D. Looney, and D. P. Mandic, "Vital signs from inside a helmet: A multichannel face-lead study'', Proceedings of ICASSP'15, pp. 982-986, 2015. [pdf]
  14. K. B. Mikkelsen, S. L. Kappel, D. P. Mandic, and P. Kidmose, "EEG recorded from the ear: Characterizing the Ear-EEG method'', Frontiers in Neuroscience, vol. 9, article 438, pp. 1-8, 2015. [pdf]
  15. J. Duun-Henriksen, T. W. Kjaer, D. Looney, M. D. Atkins, J. A. Sorensen, M. Rose, D. P. Mandic, R. E. Madsen and C. Juhl, "EEG signal quality of a subcutaneous recording system compared to standard surface electrodes'', Journal of Sensors, Article ID 167145, pp. 1--11, 2015. [pdf]
  16. V. Goverdovsky, D. Looney, P. Kidmose, C. Papavassiliou, and D. P. Mandic, "Co-located multimodal sensing: A next generation solution for wearable health'', IEEE Sensors Journal, vol. 15, no. 1, pp. 138-145, 2015. [pdf]
  17. D. Looney, P. Kidmose, M. Morrell, and D. P. Mandic, "Ear-EEG: Continuous Brain Monitoring'', in C. Guger et al. (editors), Brain-Computer Interface Research, pp. 63-71, Springer, 2014. [pdf]
  18. D. Looney, P. Kidmose, and D. P. Mandic, "Ear-EEG: User-centered and wearable BCI''', in C. Guger et al. (editors), ``Brain-Computer Interface Research}, pp. 41--50, Springer, 2014. [pdf]
  19. C. Park, C. Cheong Took, and D. P. Mandic, "Augmented complex common spatial patterns for classification of noncircular EEG from motor imagery tasks'', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 22, no. 1, pp. 1-10, 2014. [pdf]
  20. V. Goverdovsky, D. Looney, P. Kidmose, and D. P. Mandic, "Multimodal physiological sensor for motion artefact rejection'', in Proceedings of the IEEE Annual EMBC Conference, EMBC'14, pp. 2753-2756, 2014. [pdf]
  21. P. Kidmose, D. Looney, M. L. Rank, M. Ungstrup, and D. P. Mandic, "A study of evoked potentials from Ear-EEG'', IEEE Transactions on Biomedical Engineering, vol. 60, no. 10, pp. 2824-2830, 2013. [pdf]
  22. D. Looney, P. Kidmose, C. Park, M. Ungstrup, M. L. Rank, K. Rosenkranz and D. P. Mandic, "The In-the-Ear recording concept'', IEEE Pulse Magazine, vol. 3, no. 6, pp. 32-42, 2012. [pdf]
  23. D. Looney, C. Park, P. Kidmose, M. L. Rank, M. Ungstrup, and D. P. Mandic, "An in-the-ear platform for recording electroencephalogram'', in Proceedings of IEEE EBMC'11, pp. 6882-6885, 2011. [pdf]
  24. C. Park, D. Looney, P. Kidmose, M. Ungstrup, and D. P. Mandic, "Time-frequency analysis of EEG asymmetry using bivariate empirical mode decomposition'', IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 19, no. 4, pp. 366-373, 2011. [pdf]
  25. T. Rutkowski, A. Cichocki, D. P. Mandic, and T. Nishida, "Emotional empathy transition patterns from human brain responses in interactive communication situations'', AI & Society (invited paper), vol. 26, no. 3, pp. 301-315, 2011. [pdf]
  26. C. Park, D. Looney, and D. P. Mandic, "Estimating human response to taste using EEG'', in Proceedings of IEEE EBMC'11, pp. 6331-6334, 2011. [pdf]
  27. R. Palaniappan and D. P. Mandic, "Biometric from the brain electrical activity: A machine learning approach," IEEE Transactions in Pattern Analysis and Machine Intelligence (Special Issue on Biometrics), vol. 29, no. 4, pp. 738-742, 2007. [pdf]
  28. M. Golz, D. Sommer, and D. P. Mandic, "Establishing Gold Standard for Microsleep Detection in Car Drivers," Proc. of Monitoring Sleep and Sleepiness (MSSP), 2007. [pdf]
  29. D. Sommer, M. Chen, M. Golz, U. Trutschell and D. P. Mandic, "Fusion of State Space and Frequency Domain Features for Improved Microsleep Detection," International Journal of VLSI Signal Processing Systems, Special Issue on Data Fusion, vol. 49, pp. 329–342, 2007. [pdf]
  30. M. Chen, D. Sommer, S. L. Goh, T. Gautama, D. Obradovic, M. Golz, M. Morrell, H. Wang and D. P. Mandic, "A Novel Tool for Sequential Fusion of Nonlinear Features: A Sleep Psychology Application," Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, pp. 474-478, 2006. [pdf]