T. Nakamura, Y. D. Alqurashi, M. J. Morrell and D. P. Mandic, “Hearables: Automatic overnight sleep monitoring with standardised in-ear EEG sensor,” IEEE Transactions on Biomedical Engineering, vol. 67, Issue 1, pp. 203-212, 2020, pdf
T. Adjei, W. v. Rosenberg, T. Nakamura, T. Chanwimalueang, D. P. Mandic, "The ClassA Framework: HRV Based Assessment of SNS and PNS Dynamics Without LF-HF Controversies," Frontiers in Physiology, vol. 10, Article no. 505, 2019
Y. Alqurashi, T. Nakamura, V. Goverdovsky, J. Moss, M. Polkey, D. Mandic, and M. Morrell, “A novel in-ear sensor to determine sleep latency during the Multiple Sleep Latency Test (MSLT) in healthy adults with and without sleep restriction,” Nature and Science of Sleep, vol. 10, pp. 385-396, 2018
T. Nakamura, V. Goverdovsky, and D. P. Mandic, “In-ear EEG biometrics for feasible and readily collectable real-world person authentication,” IEEE Transactions on Information Forensics and Security, vol. 13, Issue 3, pp. 648-661, 2018
V. Goverdovsky, W. v. Rosenberg, T. Nakamura, D. Looney, D. J. Sharp, C. Papavassiliou, M. J. Morrell, and D. P. Mandic, “Hearables: Multimodal physiological in-ear sensing,” Scientific Reports, vol. 7, Issue 1, Article no. 6948, 2017
T. Nakamura, V.Goverdovsky, M. J. Morrell, and D. P. Mandic, “Automatic sleep monitoring using ear-EEG,” IEEE Journal of Translational Engineering in Health and Medicine, vol. 5, Article no. 2702558, 2017
T. Nakamura, H. J. Davies, and D. P. Mandic, “Scalable automatic sleep staging in the era of Big Data,” in Proc. the Annual Int. Conf. of the IEEE Eng. in Med. and Bio. Soc., EMBC 2019
H. J. Davies, T. Nakamura, and D. P. Mandic, “A transition probability based classification model for enhanced N1 sleep stage identification during automatic sleep stage scoring,” in Proc. the Annual Int. Conf. of the IEEE Eng. in Med. and Bio. Soc., EMBC 2019
T. Nakamura, Y. D. Alqurashi, M. J. Morrell, and D. P. Mandic, “Automatic detection of drowsiness using in-ear EEG,” in Proc. IEEE International Joint Conference on Neural Networks, IJCNN 2018
T. Nakamura, T. Adjei, Y. Alquarashi, D. Looney, M. J. Morrell, and D. P. Mandic, “Complexity science for sleep stage classification from EEG,” in Proc. IEEE International Joint Conference on Neural Networks, IJCNN 2017
T. Nakamura, H. Namba, and T. Matsumoto, “Classification of Auditory Steady-State Responses to Speech Data,” in Proc. 6th Annual International Conference IEEE EMBS NER, 2013
M.C. Yarici, H. J. Davies, T. Nakamura, I. Williams and D. P. Mandic, “Hearables: In-Ear Multimodal Brain Computer Interfacing,” in Brain-Computer Interface Research: A State-of-the-Art Summary, vol. 9, pp. 79-87, 2021
Y. Alqurashi, T. Nakamura, J. Moss, M. I. Polkey, D. P. Mandic, and M. J. Morrell, “The efficacy of a novel in-ear electroencephalography (EEG) sensor to measure overnight sleep in healthy participants,” The 2019 American Thoracic Society Inter. Conf. in Dallas, 2019
Y. Alqurashi, J. Moss, T. Nakamura, V. Goverdovsky, M. I. Polkey, D. P. Mandic, and M. J. Morrell, “The Efficacy of In-Ear Electroencephalography (EEG) to Monitor Sleep Latency and the Impact of Sleep Deprivation,” the 2017 American Thoracic Society Inter. Conf. in Washington, 2017
F. Fukaya, T. Nakamura, H. Namba, and T. Matsumoto, “A comparative study of ASSR classification problem using bipolar and monopolar EEG voltages,” the 2013 International Conference on Brain and Health Informatics, 2013
T. Nakamura, H. Namba, and T. Matsumoto, “Improving Information-Transfer Rate of Auditory Steady-State Responses Using Alpha Wave,” in Proc. 35th Annual Inter. Conf. IEEE Eng. Med. and Bio. Society (EMBC), 2013
H. Namba, T. Nakamura, and T. Matsumoto, “Classification of auditory steady-state responses incorporating alpha waves,” in Proc. 5th Int. Brain-Computer Interface meeting 2013, 2013