Characterisation and Separation of Brain Wave Signals

Neurons in the brain communicate through electrical impulses that give rise to both electrical and magnetic fields which are categorized into five different band limits. These waves can be measured outside the skull through an Electroencephalogram. The utilisation of brainwave detection in other areas such as biomedical engineering and gaming industry is yet to be explored. Categorisation of different rhythms of brainwaves and brainwave pattern analysis make it easier to identify the mental status of a person. This research aims to develop a hardware and software that is tested using function generators to simulate the EEG signal from the brain. It is observed that the initial results based on the above that the device performs as expected and hence can be used as brain wave signal measuring device.

[1]  E. Snidero,et al.  Micropatterned dry electrodes for brain-computer interface , 2007 .

[2]  Tao Zhang,et al.  EEG Physiological Signals Correlation under Condition of +Gz Accelerations , 2013, J. Multim..

[3]  Mohamed Moshrefi-Torbati,et al.  Signal processing techniques applied to human sleep EEG signals - A review , 2014, Biomed. Signal Process. Control..

[4]  Dandan Zhang,et al.  Calculation of compact amplitude-integrated EEG tracing and upper and lower margins using raw EEG data , 2013 .

[5]  H. Spekreijse,et al.  Mathematical dipoles are adequate to describe realistic generators of human brain activity , 1988, IEEE Transactions on Biomedical Engineering.

[6]  Kang Ryoung Park,et al.  Noise Reduction in Brainwaves by Using Both EEG Signals and Frontal Viewing Camera Images , 2013, Sensors.

[7]  Pedro J. García-Laencina,et al.  Efficient feature selection and linear discrimination of EEG signals , 2013, Neurocomputing.

[8]  Mario Mariani,et al.  Alteration of Cardiac Function in Patients with Temporal Lobe Epilepsy: Different Roles of EEG‐ECG Monitoring and Spectral Analysis of RR Variability , 1997, Epilepsia.

[9]  Dimitri Van De Ville,et al.  EEG source imaging of brain states using spatiotemporal regression , 2014, NeuroImage.

[10]  P. Hoole,et al.  Autism, EEG and brain electromagnetics research , 2012, 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences.

[11]  David Fitzpatrick,et al.  Neuroscience, 3rd ed. , 2004 .

[12]  Fabio Freschi.  Localization of Sources of Brain Activity: A MILP Approach , 2010, IEEE Transactions on Magnetics.

[13]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[14]  Ning-Han Liu,et al.  Recognizing the Degree of Human Attention Using EEG Signals from Mobile Sensors , 2013, Sensors.

[15]  J. Fermaglich.  Electric Fields of the Brain: The Neurophysics of EEG , 1982 .

[16]  S. Benbadis,et al.  Handbook of EEG Interpretation , 2007 .

[17]  Qing Zhang,et al.  Automatic artifacts removal from epileptic EEG using a hybrid algorithm , 2013 .

[18]  Ramesh.GP,et al.  A Body Area Network through Wireless Technology , 2014 .

[19]  Loránd Farkas,et al.  Embedded EEG Signal Acquisition Systems , 2014 .