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Calculation of Quantitative Parameters of Clinical EEG Signals by Adopting Visual Reading Methods
Sofiah A.a, Zakaria H.a
a Department of Biomedical Engineering, School of Electrical Engineering and Informatics, Institute Technology Bandung, Bandung, 40119, 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]© 2018 IEEE.Electroencephalography (EEG) is a technique that can measure the state of the brain’s bioelectric activity. In the clinical setting, EEG recording is followed by visual readings by clinicians for qualification. Visual analysis in conscious EEG records include the assessment of background rhythms and graphoelement. This visual reading is good to recognize artifacts. Unfortunately, it has several drawbacks, including its reliability among the assessors is quite low because it depends on the capabilities and experience of the interpreter. Also, if the EEG spatial resolution increases, it takes quite a long time to read. In this study, we developed an algorithm to calculate EEG signal parameters based on visual readings performed by clinicians. Quantitative parameters were calculated in the form of porterior dominant rhythm (PDR) existence, PDR frequency, PDR frequency asymmetry, PDR amplitude, PDR amplitude asymmetry, anterior-posterior gradient, beta amplitude, beta amplitude asymmetry, theta existence, and delta existence. The computation time needed to analyze all 16 channel EEG signals were about 115 seconds. To reduce the computation time, 5 minutes EEG records were manually selected from a complete records. The computation time reduced to 27 seconds without significant different on the quantitative parameters.[/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]Anterior posteriors,Clinical settings,Computation time,EEG recording,qEEG,Quantitative parameters,Spatial resolution,Visual analysis[/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]Electroencephalography (EEG),PDR,qEEG,signal processing[/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/ISESD.2018.8605482[/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]