Literature survey on applications of electroencephalography (EEG)

By using instrument known as electroencephalograph, electroencephalogram (EEG) of the human brain can be obtained. EEG is a record of postsynaptic potentials, generated by neurons. Usually, EEG is used to study the activities inside the human brain. This study gives significant assistant in medical field, especially in diagnosing and planning treatment for the brain related diseases. With the advancement of technology, the usage of EEG is now not only limited within the medical field. EEG has been used for brain-machine-interface (BCT) and neuromarketing. Therefore, the aim of this literature survey is to see the current trend of the applications of EEG. This survey is done by observing the research articles published in two well-known databases, which are IEEExplore and ScienceDirect. From this literature survey, it is found that the researches on EEG are still growing, with the area of applications is expanding.By using instrument known as electroencephalograph, electroencephalogram (EEG) of the human brain can be obtained. EEG is a record of postsynaptic potentials, generated by neurons. Usually, EEG is used to study the activities inside the human brain. This study gives significant assistant in medical field, especially in diagnosing and planning treatment for the brain related diseases. With the advancement of technology, the usage of EEG is now not only limited within the medical field. EEG has been used for brain-machine-interface (BCT) and neuromarketing. Therefore, the aim of this literature survey is to see the current trend of the applications of EEG. This survey is done by observing the research articles published in two well-known databases, which are IEEExplore and ScienceDirect. From this literature survey, it is found that the researches on EEG are still growing, with the area of applications is expanding.

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[2]  Silas Formunyuy Verkijika,et al.  Using a brain-computer interface (BCI) in reducing math anxiety: Evidence from South Africa , 2015, Comput. Educ..

[3]  Matthew R. Myers,et al.  Real-Time Detection and Monitoring of Acute Brain Injury Utilizing Evoked Electroencephalographic Potentials , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[4]  Cuntai Guan,et al.  Adaptive estimation of hand movement trajectory in an EEG based brain–computer interface system , 2015, Journal of neural engineering.

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[6]  Omar Farooq,et al.  Sweet and sour taste classification using EEG based brain computer interface , 2015, 2015 Annual IEEE India Conference (INDICON).

[7]  William C Walker,et al.  Distinction in EEG slow oscillations between chronic mild traumatic brain injury and PTSD. , 2016, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[8]  Amir Homayoun Jafari,et al.  Prediction of epileptic seizures from EEG using analysis of ictal rules on Poincaré plane , 2017, Comput. Methods Programs Biomed..

[9]  Javad Birjandtalab,et al.  Automated seizure detection using limited-channel EEG and non-linear dimension reduction , 2017, Comput. Biol. Medicine.

[10]  Erchin Serpedin,et al.  Epileptic seizure onset detection based on EEG and ECG data fusion , 2016, Epilepsy & Behavior.

[11]  Temel Kayikçioglu,et al.  Classification of EEG signal during gaze on the different rotating vanes , 2016, 2016 24th Signal Processing and Communication Application Conference (SIU).

[12]  Wanli Ma,et al.  Investigating The Impact Of Epilepsy On EEG-based Cryptographic Key Generation Systems , 2017, KES.

[13]  Murat Kaya,et al.  Detecting the attention state of an operator in continuous attention task using EEG-based brain-computer interface , 2015, 2015 23nd Signal Processing and Communications Applications Conference (SIU).

[14]  Ariel Telpaz,et al.  Using EEG to Predict Consumers’ Future Choices , 2015 .

[15]  Alexandre Noyvirt,et al.  Automatic EEG processing for the early diagnosis of Traumatic Brain Injury , 2016, 2016 World Automation Congress (WAC).

[16]  Jun Wang,et al.  An EEG-Based brain-computer interface for emotion recognition , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

[17]  A. Prasad Vinod,et al.  Detection of Familiar and Unfamiliar Images Using EEG-Based Brain-Computer Interface , 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

[18]  A. P. Vinod,et al.  Voice familiarity detection using EEG-based Brain-Computer Interface , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[19]  Sudhanshu K. Semwal,et al.  EEG headset supporting mobility impaired gamers with game accessibility , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[20]  Jordan J. Louviere,et al.  Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking , 2013, Expert Syst. Appl..

[21]  Zhi-Hong Mao,et al.  Brain-computer interface combining eye saccade two-electrode EEG signals and voice cues to improve the maneuverability of wheelchair , 2017, 2017 International Conference on Rehabilitation Robotics (ICORR).

[22]  Lin Wang,et al.  My destination in your brain: A novel neuromarketing approach for evaluating the effectiveness of destination marketing , 2016 .

[23]  Wen-Wen Chang,et al.  Functional brain network and multichannel analysis for the P300-based brain computer interface system of lying detection , 2016, Expert Syst. Appl..

[24]  Tao Zhang,et al.  Automatic epileptic EEG detection using DT-CWT-based non-linear features , 2017, Biomed. Signal Process. Control..

[25]  J. McBride,et al.  Classification of traumatic brain injury using support vector machine analysis of event-related Tsallis entropy , 2011, Proceedings of the 2011 Biomedical Sciences and Engineering Conference: Image Informatics and Analytics in Biomedicine.

[26]  Enas W. Abdulhay,et al.  Automated diagnosis of epilepsy from EEG signals using ensemble learning approach , 2017, Pattern Recognit. Lett..

[27]  Dong Liu,et al.  An EEG-based brain-computer interface for gait training , 2017, 2017 29th Chinese Control And Decision Conference (CCDC).

[28]  Cheng-Wei Lin,et al.  An brain-computer interface for video content analysis system for perceive emotions by using EEG , 2016, 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW).

[29]  Debi Prosad Dogra,et al.  Analysis of EEG signals and its application to neuromarketing , 2017, Multimedia Tools and Applications.

[30]  Suchismita Chinara,et al.  An application of wireless brain–computer interface for drowsiness detection , 2016 .

[31]  M. Murugappan,et al.  Wireless EEG signals based Neuromarketing system using Fast Fourier Transform (FFT) , 2014, 2014 IEEE 10th International Colloquium on Signal Processing and its Applications.

[32]  M. L. Dewal,et al.  Wavelet entropy based EEG analysis for seizure detection , 2013, 2013 IEEE International Conference on Signal Processing, Computing and Control (ISPCC).

[33]  José Luis Contreras-Vidal,et al.  EEG-based brain-computer interface to a virtual walking avatar engages cortical adaptation , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[34]  L. D. de Vries,et al.  Rhythmic EEG patterns in extremely preterm infants: Classification and association with brain injury and outcome , 2017, Clinical Neurophysiology.

[35]  I. Obeid,et al.  Assessing traumatic brain injuries using EEG power spectral analysis and instantaneous phase , 2012, 2012 38th Annual Northeast Bioengineering Conference (NEBEC).

[36]  J. Kosters.  Prediction of preference and choice of wines by EEG derived measures during taste and smell procedures. , 2017 .

[37]  Francisco Velasco-Álvarez,et al.  Audio-Cued SMR Brain-Computer Interface to Drive a Virtual Wheelchair , 2011, IWANN.

[38]  Bülent Yilmaz,et al.  Like/dislike analysis using EEG: Determination of most discriminative channels and frequencies , 2014, Comput. Methods Programs Biomed..

[39]  Sampsa Vanhatalo,et al.  Evoked potentials recorded during routine EEG predict outcome after perinatal asphyxia , 2017, Clinical Neurophysiology.

[40]  G. Variane,et al.  Early amplitude-integrated electroencephalography for monitoring neonates at high risk for brain injury. , 2017, Jornal de pediatria.

[41]  Yuan-Hao Huang,et al.  An HMM-based eye movement detection system using EEG brain-computer interface , 2014, 2014 IEEE International Symposium on Circuits and Systems (ISCAS).

[42]  Kwang Suk Park,et al.  An amplitude-modulated visual stimulation for reducing eye fatigue in SSVEP-based brain–computer interfaces , 2014, Clinical Neurophysiology.

[43]  Slawomir J. Nasuto,et al.  Movement intention based Brain Computer Interface for Virtual Reality and Soft Robotics rehabilitation using novel autocorrelation analysis of EEG , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[44]  Tarmo Lipping,et al.  Prediction of outcome in traumatic brain injury patients using long-term qEEG features , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[45]  Yan Li,et al.  Classify epileptic EEG signals using weighted complex networks based community structure detection , 2017, Expert Syst. Appl..

[46]  Yang Yu,et al.  A novel Morse code-inspired method for multiclass motor imagery brain-computer interface (BCI) design , 2015, Comput. Biol. Medicine.

[47]  N. K. Cauvery,et al.  Real-time EEG based object recognition system using Brain Computer Interface , 2014, 2014 International Conference on Contemporary Computing and Informatics (IC3I).

[48]  Zhang Weidong,et al.  Deep learning EEG response representation for brain computer interface , 2015, 2015 34th Chinese Control Conference (CCC).