Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/16747
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dc.contributor.authorHui, Sheldon.-
dc.date.accessioned2009-05-28T03:20:08Z-
dc.date.available2009-05-28T03:20:08Z-
dc.date.copyright2009en_US
dc.date.issued2009-
dc.identifier.urihttp://hdl.handle.net/10356/16747-
dc.description.abstractVictims of accidents are often permanently disabled due to nerve damage or loss of limbs. One solution to assist the paralyzed or “locked-in” patients is to implement automated assisted motion through Brain-Computer Interface (BCI) technology. To date, however, BCI is still in developmental stages due to difficulties of interpreting actual patient requests. Some of the most successful attempts at implementing BCI exercised the use of Steady State Evoked Potentials (SSVEPs) to translate human thoughts into palpable commands for control purpose Visual Evoked Potentials are electrical impulse responses from the visual cortex of the human brain under visual stimulation. Since evoked potentials are considerably weaker than typical brain rhythms, the Steady-State VEPs are considered among the most reliable forms of bioelectrical signals that can be retrieved from the brain due to their periodicity and relatively high signal-to-noise ratio. The first part of this report elaborates on the theoretical background of SSVEPs and the principles of neuroscience. This project seeks to investigate the characteristics and reliability of the SSVEP for biomedical engineering purposes. Experiments have been conducted over different subjects with the aim of retrieving stimulated SSVEP responses from their Electroencephalography (EEG) signals. These tests have been planned to observe variations in the SSVEP responses under different stimulation conditions, such as color and environmental disturbances. The procedures and results for these experiments are documented in the second half of this report. Finally, this report concludes by discussing the discovery achieved from these experiments, highlighting recommended enhancements to these tests. The ultimate goal of this project is to acquire knowledge in the complex field of neuroscience, so as generate new ideas beneficial to humanity.en_US
dc.format.extent80 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University-
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronicsen_US
dc.titleElectroencephalography signal processingen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorSong Qingen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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