|
[1]
|
He, Z., Yang, K., Zhuang, N. and Zeng, Y. (2021) Processing of Affective Pictures: A Study Based on Functional Con-nectivity Network in the Cerebral Cortex. Computational Intelligence and Neuroscience, 2021, Article ID: 5582666. [Google Scholar] [CrossRef] [PubMed]
|
|
[2]
|
Gkintoni, E., Meintani, P.M. and Dimakos, I. (2021) Neurocognitive and Emotional Parameters in Learning and Educational Process. 14th Annual International Conference of Education, Re-search and Innovation, Online, 8-9 November 2021, 2588-2599. [Google Scholar] [CrossRef]
|
|
[3]
|
Bruner, E., Battaglia-Mayer, A. and Caminiti, R. (2023) The Parietal Lobe Evolution and the Emergence of Material Culture in the Human Genus. Brain Structure and Function, 228, 145-167. [Google Scholar] [CrossRef] [PubMed]
|
|
[4]
|
Palejwala, A.H., O’Connor, K.P., Pelargos, P., Briggs, R.G., Milton, C.K., Conner, A.K., Milligan, T.M., O’Donoghue, D.L., Glenn, C.A. and Sughrue, M.E. (2020) Anatomy and White Matter Connections of the Lateral Occipital Cortex. Surgical and Radiologic Anatomy, 42, 315-328. [Google Scholar] [CrossRef] [PubMed]
|
|
[5]
|
Doherty, C., Nowacki, A.S., Pat McAndrews, M., McDonald, C.R., Reyes, A., Kim, M.S., Hamberger, M., Najm, I., Bingaman, W., Jehi, L. and Busch, R.M. (2021) Predicting Mood Decline Following Temporal Lobe Epilepsy Surgery in Adults. Epilepsia, 62, 450-459. [Google Scholar] [CrossRef] [PubMed]
|
|
[6]
|
Fu, Z., Wu, D.-A.J., Ross, I., Chung, J.M., Mamelak, A.N., Adolphs, R. and Rutishauser, U. (2019) Single-Neuron Correlates of Error Monitoring and Post-Error Adjustments in Human Medial Frontal Cortex. Neuron, 101, 165-177. [Google Scholar] [CrossRef] [PubMed]
|
|
[7]
|
庄宁. 基于脑电的情绪加工与识别技术研究[D]: [博士学位论文]. 北京: 战略支援部队信息工程大学, 2020.
|
|
[8]
|
Songsamoe, S., Saengwong-ngam, R., Koomhin, P. and Matan, N. (2019) Understanding Consumer Physiological and Emotional Responses to Food Products Using Electroen-cephalography (EEG). Trends in Food Science and Technology, 93, 167-173. [Google Scholar] [CrossRef]
|
|
[9]
|
Lai, C.Q., Ibrahim, H., Abdullah, M.Z., Abdullah, J.M., Suandi, S.A. and Azman, A. (2018) Literature Survey on Applications of Electroencephalography (EEG). AIP Conference Pro-ceedings, 2016, Article ID: 020070. [Google Scholar] [CrossRef]
|
|
[10]
|
Jebelli, H., Hwang, S. and Lee, S. (2018) EEG Signal-Processing Frame-work to Obtain High-Quality Brain Waves from an Off-the-Shelf Wearable EEG Device. Journal of Computing in Civil Engineering, 32, Article ID: 04017070. [Google Scholar] [CrossRef]
|
|
[11]
|
Prabhu, S., Murugan, G., Cary, M., Arulperumjothi, M. and Liu, J.-B. (2020) On Certain Distance and Degree Based Topological Indices of Zeolite LTA Frameworks. Mate-rials Research Express, 7, Article ID: 055006. [Google Scholar] [CrossRef]
|
|
[12]
|
Motamedi-Fakhr, S., Moshrefi-Torbati, M., Hill, M., Hill, C.M. and White, P.R. (2014) Signal Processing Techniques Applied to Human Sleep EEG Signals—A Review. Biomedical Signal Processing and Control, 10, 21-33. [Google Scholar] [CrossRef]
|
|
[13]
|
Ramanujam, B., Dash, D. and Tripathi, M. (2018) Can Home Videos Made on Smartphones Complement Video-Eeg in Diagnosing Psychogenic Nonepileptic Seizures? Seizure, 62, 95-98. [Google Scholar] [CrossRef] [PubMed]
|
|
[14]
|
Davis, F.D., Riedl, R., vom Brocke, J., Léger, P.M. and Randolph, A.B. (2016) Information Systems and Neuroscience: Gmunden Retreat on NeuroIS 2016. Springer, Cham. [Google Scholar] [CrossRef]
|
|
[15]
|
李培楠, 包为民, 姚伟. 工程科学发展战略问题与机制完善[J]. 中国科学院院刊, 2022, 37(3): 317-325.
|
|
[16]
|
Lafon, B., Henin, S., Huang, Y., Friedman, D., Melloni, L., Thesen, T., Doyle, W., Buzsáki, G., Devinsky, O., Parra, L.C. and Liu, A.A. (2017) Low Frequency Transcranial Electrical Stimula-tion Does Not Entrain Sleep Rhythms Measured by Human Intracranial Recordings. Nature Communications, 8, No. 1199. [Google Scholar] [CrossRef] [PubMed]
|
|
[17]
|
Bleichner, M.G. and Debener, S. (2017) Concealed, Unobtrusive Ear-Centered EEG Acquisition: CEEGrids for Transparent EEG. Frontiers in Human Neuroscience, 11, Article 163. [Google Scholar] [CrossRef] [PubMed]
|
|
[18]
|
Kumar, J.S. and Bhuvaneswari, P. (2012) Analysis of Electroen-cephalography (EEG) Signals and Its Categorization—A Study. Procedia Engineering, 38, 2525-2536. [Google Scholar] [CrossRef]
|
|
[19]
|
Mehmood, R.M. and Lee, H.J. (2016) A Novel Feature Extrac-tion Method Based on Late Positive Potential for Emotion Recognition In Human Brain Signal Patterns. Computers and Electrical Engineering, 53, 444-457. [Google Scholar] [CrossRef]
|
|
[20]
|
Peterson, V., Galván, C., Hernández, H. and Spies, R. (2020) A Feasibility Study of a Complete Low-Cost Consumer-Grade Brain-Computer Interface System. Heliyon, 6, e03425. [Google Scholar] [CrossRef] [PubMed]
|
|
[21]
|
Wulandari, D.P., Putri, N.G.P., Suprapto, Y.K., Pur-nami, S.W., Juniani, A.I. and Islamiyah, W.R. (2019) Epileptic Seizure Detection Based on Bandwidth Features of EEG Signals. Procedia Computer Science, 161, 568-576. [Google Scholar] [CrossRef]
|
|
[22]
|
Riedl, R. and Léger, P.-M. (2016) Fundamentals of NeuroIS: In-formation Systems and the Brain. Springer, Berlin. [Google Scholar] [CrossRef]
|
|
[23]
|
Golnar-Nik, P., Farashi, S. and Safari, M.S. (2019) The Applica-tion of EEG Power for the Prediction and Interpretation of Consumer Decision-Making: A Neuromarketing Study. Physiology and Behavior, 207, 90-98. [Google Scholar] [CrossRef] [PubMed]
|
|
[24]
|
Hsu, L. and Chen, Y.-J. (2020) Neuromarketing, Subliminal Advertising, and Hotel Selection: An EEG Study. Australasian Marketing Journal, 28, 200-208. [Google Scholar] [CrossRef]
|
|
[25]
|
Buettner, R., Rieg, T. and Frick, J. (2020) Machine Learning Based Diagnosis of Diseases Using the Unfolded EEG Spectra: Towards an Intelligent Software Sensor. In: Davis, F., Riedl, R., vom Brocke, J., Léger, P.-M., Randolph, A. and Fischer, T., Eds., Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, Vol. 32, Springer, Cham, 165-172. [Google Scholar] [CrossRef]
|
|
[26]
|
Marchi, N., Granata, T. and Janigro, D. (2014) Inflammatory Pathways of Seizure Disorders. Trends in Neurosciences, 37, 55-65. [Google Scholar] [CrossRef] [PubMed]
|
|
[27]
|
Kumar, Y., Dewal, M.L. and Anand, R.S. (2013) Wavelet Entropy Based EEG Analysis for Seizure Detection. 2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC), Solan, 26-28 September 2013, 1-6. [Google Scholar] [CrossRef]
|
|
[28]
|
Cai, H., Han, J., Chen, Y., Sha, X., Wang, Z., Hu, B., Yang, J., Feng, L., Ding, Z., Chen, Y. and Gutknecht, J. (2018) A Perva-sive Approach to EEG-Based Depression Detection. Complexity, 2018, Article ID: 5238028. [Google Scholar] [CrossRef]
|
|
[29]
|
Peveler, R., Carson, A. and Rodin, G. (2002) Depression in Medical Patients. BMJ, 325, 149-152. [Google Scholar] [CrossRef] [PubMed]
|
|
[30]
|
Mcintyre, R.S. and O’Donovan, C. (2004) The Human Cost of Not Achieving Full Remission in Depression. Canadian Journal of Psychiatry, 49, 10S-16S.
|
|
[31]
|
Hasanzadeh, F., Mohebbi, M. and Rostami, R. (2019) Prediction of rTMS Treatment Response in Major Depressive Disorder Using Machine Learning Techniques and Nonlinear Features of EEG Signal. Journal of Affective Disorders, 256, 132-142. [Google Scholar] [CrossRef] [PubMed]
|
|
[32]
|
Smitha, K.G., Vinod, A.P. and Mahesh, K. (2017) Voice Familiarity Detection Using EEG-Based Brain-Computer Interface. 2016 IEEE International Conference on Systems, Man, and Cy-bernetics (SMC), Budapest, 9-12 October 2016, 1626-1631. [Google Scholar] [CrossRef]
|
|
[33]
|
Tezza, D., Caprio, D., Garcia, S., Pinto, B., Laesker, D. and Andujar, M. (2020) Brain-Controlled Drone Racing Game: A Qualitative Analysis. In: Fang, X., Ed., HCI in Games. HCII 2020. Lecture Notes in Computer Science, Vol. 12211, Springer, Cham, 350-360. [Google Scholar] [CrossRef]
|
|
[34]
|
Sood, S.K. and Singh, K.D. (2018) An Optical-Fog Assisted EEG-Based Virtual Reality Framework for Enhancing E-Learning through Educational Games. Computer Applications in Engineering Education, 26, 1565-1576. [Google Scholar] [CrossRef]
|
|
[35]
|
Galán, F., Nuttin, M., Lew, E., Ferrez, P.W., Vanacker, G., Philips, J. and del R. Millán, J. (2008) A Brain-Actuated Wheelchair: Asynchronous and Non-Invasive Brain-Computer Interfaces for Continuous Control of Robots. Clinical Neurophysiology, 119, 2159-2169. [Google Scholar] [CrossRef] [PubMed]
|
|
[36]
|
Liu, T., Goldberg, L., Gao, S. and Hong, B. (2010) An Online Brain-Computer Interface Using Non-Flashing Visual Evoked Potentials. Journal of Neural Engineering, 7, Article ID: 036003. [Google Scholar] [CrossRef] [PubMed]
|
|
[37]
|
Zhao, Q., Zhang, L. and Cichocki, A. (2009) EEG-Based Asynchronous BCI Control of a Car in 3D Virtual Reality Environments. Chinese Science Bulletin, 54, 78-87. [Google Scholar] [CrossRef]
|
|
[38]
|
Kasim, M.A.A., Low, C.Y., Ayub, M.A., Zakaria, N.A.C., Salleh, M.H.M., Johar, K. and Hamli, H. (2017) User-Friendly LabVIEW GUI for Prosthetic Hand Control Using Emotiv EEG Headset. Procedia Computer Science, 105, 276-281. [Google Scholar] [CrossRef]
|
|
[39]
|
晁浩, 刘永利, 连卫芳. EEG情感识别中基于集成深度学习模型的多分析域特征融合[J]. 控制与决策, 2020, 35(7): 1674-1680.
|
|
[40]
|
Khushaba, R.N., Wise, C., Kodagoda, S., Louviere, J., Kahn, B.E. and Townsend, C. (2013) Consumer Neuroscience: Assessing the Brain Response to Marketing Stimuli Using Electroencephalogram (EEG) and Eye Tracking. Expert Systems with Applications, 40, 3803-3812. [Google Scholar] [CrossRef]
|
|
[41]
|
Ćosić, D. (2016) Neuromarketing in Market Research. Interdisciplinary Description of Complex Systems, 14, 139-147. [Google Scholar] [CrossRef]
|
|
[42]
|
Bastiaansen, M., Straatman, S., Driessen, E., Mitas, O., Stekelenburg, J. and Wang, L. (2018) My Destination in Your Brain: A Novel Neuromarketing Approach for Evaluating the Effectiveness of Destination Marketing. Journal of Destination Marketing & Management, 7, 76-88. [Google Scholar] [CrossRef]
|
|
[43]
|
Tromp, J., Peeters, D., Meyer, A.S. and Hagoort, P. (2018) The Combined Use of Virtual Reality and EEG to Study Language Processing in Naturalistic Environments. Behavior Re-search Methods, 50, 862-869. [Google Scholar] [CrossRef] [PubMed]
|
|
[44]
|
D’Errico, F., Leone, G., Schmid, M. and D’Anna, C. (2020) Prosocial Virtual Reality, Empathy, and EEG Measures: A Pilot Study Aimed at Monitoring Emotional Processes in In-tergroup Helping Behaviors. Applied Sciences, 10, Article No. 1196. [Google Scholar] [CrossRef]
|
|
[45]
|
Lin, F.R. and Kao, C.M. (2018) Mental Effort Detection Using EEG Data in E-Learning Contexts. Computers and Education, 122, 63-79. [Google Scholar] [CrossRef]
|
|
[46]
|
Chen, J., Li, H., Ma, L., Bo, H. and Gao, X. (2020) Application of EEMD-HHT Method on EEG Analysis for Speech Evoked Emotion Recognition. 2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), Shenzhen, 6-8 August 2020, 376-381. [Google Scholar] [CrossRef]
|