Non-invasive detection of Ketum users through objective analysis of EEG signals
Document Type
Conference Item
Publication Date
11-1-2021
Abstract
Ketum leaves are traditionaly used for treatment of backpain and reduce fatigue. However, in recent years people use ketum leaves to substitute traditional drugs as they can easily be obtained at a low cost. Currently, a robust test for ketum detection is not available. Although ketum usage detection via test strip is available, however, the method is possible to be polluted by other substances and can be manipulated. Brain signals have unique characteristics and are well-known as a robust method for recognition and disease detection. Thus, this study has been done to distinguish between ketum users and non-users via brain signal characteristics. Eight participants were chosen, four of whom are heavy ketum users and four non-users with no health issues. Data were collected using the eegoSports device in relaxed state. In pre-processing, notch filter and Independent Component Analysis (ICA) were used to remove artifacts. Wavelet Packet Transform (WPT) was used to reduce the large data dimension and extract features from the brain signal. To select the most significant features, T-Test was used. Support Vector Machine (SVM), K-Nearest Neighbour, and Ensemble classifier were used to categorize the input data into ketum users and non-users. Ensemble classifier was found to be able to predict the testing instances with 100 accuracy for open and closed eyes task with Teager energy and energy to standard deviation ratio as the features. © 2021 Institute of Physics Publishing. All rights reserved.
Keywords
Ketum leaves, Substutite drug, Brain signals, Non-invasive detection, EEG signals
Divisions
psychological
Funders
Research Materials Fund,Universiti Malaysia Perlis [Grant No.: 9001-00626]
Publication Title
Journal of Physics: Conference Series
Volume
2071
Issue
1
Event Title
2021 International Conference on Biomedical Engineering, ICoBE 2021
Event Location
Virtual, Online
Event Dates
14 - 15 September 2021
Event Type
conference