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Framework for Electroencephalography-based Evaluation of User Experience [PDF]

, 2016
Measuring brain activity with electroencephalography (EEG) is mature enough to assess mental states. Combined with existing methods, such tool can be used to strengthen the understanding of user experience.
Cutrell Edward, Frey Jérémy, Hoffmann Ulrich, Kivikangas J. Matias, Pike Matthew, Wobrock Dennis   +5 more
core   +5 more sources

Head phantoms for electroencephalography and transcranial electric stimulation: a skull material study [PDF]

Hunold, A., Strohmeier, D., Fiedler, P., et al. (2017). Head phantoms for electroencephalography and transcranial electric stimulation: a skull material study. Biomedical Engineering / Biomedizinische Technik, 0(0), pp. -, 2018
Physical head phantoms allow assessing source reconstruction procedures in electroencephalography and electrical stimulation profiles during transcranial electric stimulation. Volume conduction in the head is strongly influenced by the skull representing
Fiedler, Patrique, Haueisen, Jens, Hunold, Alexander, Strohmeier, Daniel   +3 more
core   +2 more sources

Electroencephalography Signal Processing: A Comprehensive Review and Analysis of Methods and Techniques

Italian National Conference on Sensors, 2023
The electroencephalography (EEG) signal is a noninvasive and complex signal that has numerous applications in biomedical fields, including sleep and the brain–computer interface.
A. Chaddad, Yihang Wu, R. Kateb, A. Bouridane   +3 more
semanticscholar   +1 more source

Associations Between Infant Screen Use, Electroencephalography Markers, and Cognitive Outcomes

JAMA pediatrics, 2023
This cohort study analyzes data for children from the population-based study Growing Up in Singapore Toward Healthy Outcomes (GUSTO) to examine the associations between infant screen time, electroencephalography markers, and school-age cognitive outcomes
Law Ec, Han Mx, Lai Z, Lim S, Ong Zy, Ng V, Gabard-Durnam Lj, Wilkinson Cl, Levin Ar, Rifkin-Graboi A, Daniel Lm, Gluckman Pd, Chong Ys, Meaney Mj, Nelson Ca   +14 more
semanticscholar   +1 more source

Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification [PDF]

AAAI Conference on Artificial Intelligence, 2021
State-of-the-art brain-to-text systems have achieved great success in decoding language directly from brain signals using neural networks. However, current approaches are limited to small closed vocabularies which are far from enough for natural ...
Zhenhailong Wang, Heng Ji
semanticscholar   +1 more source

The International Cardiac Arrest Research Consortium Electroencephalography Database

Critical Care Medicine, 2023
OBJECTIVES: To develop the International Cardiac Arrest Research (I-CARE), a harmonized multicenter clinical and electroencephalography database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.
MD Edilberto Amorim, PhD Wei-Long Zheng, PhD Mohammad M. Ghassemi, MSc Mahsa Aghaeeaval, PhD Pravinkumar Kandhare, Vishnu Karukonda, Ba, MD PhD Jong Woo Lee, MD Susan T. Herman, MD Adithya Sivaraju, MD PhD Nicolas Gaspard, MD PhD Jeannette Hofmeijer, MD PhD Michel J. A. M. van Putten, PhD Reza Sameni, PhD Matthew A. Reyna, DPhil Gari D. Clifford, M. P. M. Brandon Westover   +16 more
semanticscholar   +1 more source

Deep learning-based electroencephalography analysis: a systematic review [PDF]

Journal of Neural Engineering, 2019
Context. Electroencephalography (EEG) is a complex signal and can require several years of training, as well as advanced signal processing and feature extraction methodologies to be correctly interpreted.
Yannick Roy, Hubert J. Banville, Isabela Albuquerque, Alexandre Gramfort, T. Falk, J. Faubert   +5 more
semanticscholar   +1 more source

Adhesive Wearable Sensors for Electroencephalography from Hairy Scalp

Advanced Healthcare Materials, 2023
Electroencephalography has garnered interest for applications in mobile healthcare, human–machine interfaces, and Internet of Things. Conventional electroencephalography relies on wet and dry electrodes.
A. Zhang, Abhijith Balamuraleekrishna Shyam, Alexandra Cunningham, Chris Williams, Amanda J Brissenden, Alex Bartley, B. Amsden, A. Docoslis, M. Kontopoulou, S. K. Ameri   +9 more
semanticscholar   +1 more source

Resilience Aspects in Distributed Wireless Electroencephalographic Sampling [PDF]

2020 9th Mediterranean Conference on Embedded Computing (MECO), 2020, pp. 1-7, 2022
Resilience aspects of remote electroencephalography sampling are considered. The possibility to use motion sensors data and measurement of industrial power network interference for detection of failed sampling channels is demonstrated. No significant correlation between signals of failed channels and motion sensors data is shown.
arxiv   +1 more source

Brain functional and effective connectivity based on electroencephalography recordings: A review

Human Brain Mapping, 2021
Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional ...
Jun Cao, Yifan Zhao, Xiaocai Shan, Hualiang Wei, Yuzhu Guo, Liangyu Chen, J. Erkoyuncu, P. Sarrigiannis   +7 more
semanticscholar   +1 more source