Abstract
In recent years, scientists have investigated the potential of EEG for identifying emotional states. Analyzing the patterns and frequencies of brainwave activity makes it possible to detect and classify different emotional states, such as happiness, sadness, fear, or anger. In daily life, it is evident that there are differences in how men and women think and approach various aspects, such as perceiving and experiencing emotions. Given the scarcity of research on gender-based EEG studies, it is crucial to explore this area to gain valuable insights into the unique neurological aspects of gender. This study examines gender disparities in emotion recognition using the Hjorth Parameter analysis. This study recorded the data of 24 healthy subjects (22± 5.6 years old) using a wireless OpenBCI EEG device. The participants were stimulated by seeing happy and sad videos. The electrodes used in this study were placed in the frontal area channels F7, F8, FP1, and FP2, following the internationally recognized 10/20 EEG system. EEG pre-processing techniques include signal filtering and ICA for Artifact removal. The EEG signals were separated into alpha, beta, and gamma sub-bands using Butterworth filters. The analysis was to compute the Hjorth parameters: in activity, mobility, and complexity. We used the Fisher ratio to identify the most influential features, then processed and analyzed them using SVM, KNN, Naive Bayes, and Random Forest algorithms for emotion classification. This study has shown that Hjorth Activity outperforms other Hjorth parameters, such as Hjorth mobility and complexity, in accurately recognizing emotions, and the beta subband is the most sensitive in distinguishing between happy and sad emotions. On the gender aspect, differences in emotional responses between men and women are evident. Women tend to exhibit more similar EEG patterns among themselves, while men show more significant individual differences. The other intriguing finding is that the value of the gamma subband is higher for both men and women in the sad condition, indicating that the cognitive process appears more evolved than in the happy condition.
| Original language | English |
|---|---|
| Title of host publication | IES 2023 - International Electronics Symposium |
| Subtitle of host publication | Unlocking the Potential of Immersive Technology to Live a Better Life, Proceeding |
| Editors | Andhik Ampuh Yunanto, Afifah Dwi Ramadhani, Yanuar Risah Prayogi, Putu Agus Mahadi Putra, Maretha Ruswiansari, Mohamad Ridwan, Farida Gamar, Weny Mistarika Rahmawati, Rusli Muhammad Rusli, Fitrah Maharani Humaira, Ahmad Firyal Adila |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 179-185 |
| Number of pages | 7 |
| ISBN (Electronic) | 9798350314731 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 25th International Electronics Symposium, IES 2023 - Denpasar, Indonesia Duration: 8 Aug 2023 → 10 Aug 2023 |
Publication series
| Name | IES 2023 - International Electronics Symposium: Unlocking the Potential of Immersive Technology to Live a Better Life, Proceeding |
|---|
Conference
| Conference | 25th International Electronics Symposium, IES 2023 |
|---|---|
| Country/Territory | Indonesia |
| City | Denpasar |
| Period | 8/08/23 → 10/08/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 5 Gender Equality
Keywords
- Cognitive Process
- EEG
- Emotion Recognition
- Fisher Ratio
- Gamma Subband
- Gender-based
- Hjorth Parameter
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