Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156478
Title: An affective BCI system with music in an immersive environment
Authors: Khendry, Nishka
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Science::Medicine::Biomedical engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Khendry, N. (2022). An affective BCI system with music in an immersive environment. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156478
Project: SCSE21-0028
Abstract: This study investigates the effectiveness of generated music in a Virtual reality (VR) immersive environment in inducing different emotional arousal states in the context of alleviating mood disorders. It details the collection and labelling of EEG data from 20 participants which is evaluated using two state-of-the-art EEG emotion classification models – TSception and EEGNet. This report outlines the end-to-end implementation of a novel data recording system combining Python-based music generation, VR development with Unity, and EEG data streaming and labelling. It also highlights the overall system design considerations and experiment protocols administered. Given a fixed high valence value, the labelled EEG data recorded was used for offline model training to classify three emotional arousal states – low, high, and neutral. High classification accuracies were reported for Low-High arousal classification - 81.57% for TSception and 83.45% for EEGNet. Therefore, it can be concluded that the EEG data collected contained distinctive emotional states. This system, combining the effect of VR and music, is effective in inducing emotional arousal states and can be explored further in clinical trials as a potential tool for emotion modulation in alleviating mood disorders.
URI: https://hdl.handle.net/10356/156478
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Amended_FYP_Report_KhendryNishka.pdf
  Restricted Access
2.59 MBAdobe PDFView/Open

Page view(s)

22
Updated on May 19, 2022

Download(s)

4
Updated on May 19, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.