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Steady-State Visual Evoked Potential based Brain Computer Interface: Experiment of LED stimulation in two-rooms condition
Wicaksono N.B.a, Mengko T.L.R.b, Suprijantob
a Department of Medical Instrumentation, Politeknik Mekatronika Sanata Dharma, Yogyakarta, Indonesia
b School of Electrical and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2015 IEEE.The aim of this study is to determine the effect of room’s light condition to brain response. Brain response to repetitive visual stimulation is called Steady-State Visual Evoked Potential (SSVEP) based Brain-Computer Interface (BCI). In this study, flickering Light Emitting Diode (LED) is used as visual stimulation. Mostly, brain response is recorded using electroencephalograph (EEG) and recorded in the brain’s occipital lobe that is associated with human vision. Welch’s method of power spectral estimation is implemented for estimating the power spectral of recorded signal. The result shows that the highest-power of brain response to repetitive visual stimulus can be detected either in the dark-room or in the bright-room.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Light conditions,Power detection,Power spectral,Power spectral estimation,Recorded signals,Steady state visual evoked potentials,Visual stimulation,Visual stimulus[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Brain-Computer Interface (BCI),Highest-Power Detection,LED Visual Stimulation,Power Spectral Estimation,Steady-State Visual Evoked Potential (SSVEP)[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICICI-BME.2015.7401341[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]