@inproceedings{01a2368f9006436790be57a914700d3d,
title = "EEG-P300 Potential in Methadone Subjects based on Parietal and Frontal Channels with Different Image Stimulus",
abstract = "Methadone is a class of drug relating to the opium analgesic class. This drug is used as a substitute for narcotic drugs that make addiction. In this paper, we use EEG-P300 Signals to investigate influence in Methadone subject with stimuli to view responses of electrical potential. Nineteen subjects consist of two groups (methadone and control) are involved in the experiment. The extraction features used wavelet Coefficient 5 level 5 for EEG signal processing. Finally, the EEG-P300 potential and its latency are evaluated and compared by the control subject based on parietal and frontal channels. The result showed that potential control higher than methadone, it causes by Dysfunctional impulsivity in frontal cortex.",
keywords = "EEG, Frontal, Methadone, P300, Parietal, Wavelet",
author = "Kusumandari, {Dwi E.} and Suhendra, {M. Agung} and Rizqyawan, {M. Ilham} and U. Ulfah and Simbolon, {Artha I.} and Rina Ristiana and Arjon Turnip and Sobana, {Siti Aminah} and Istiqomah, {Arifah Nur}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd International Conference of Computer Science and Information Technology, ICoSNIKOM 2019 ; Conference date: 28-11-2019 Through 29-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ICoSNIKOM48755.2019.9111484",
language = "English",
series = "2019 International Conference of Computer Science and Information Technology, ICoSNIKOM 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 International Conference of Computer Science and Information Technology, ICoSNIKOM 2019",
address = "United States",
}