Analysis of EEG Signals and Facial Expressions for Continuous Emotion Detection


Emotions are time varying affective phenomena that are elicited as a result of stimuli. Videos and films in particular are made to elicit emotions in their audiences. Detecting the viewers' emotions instantaneously will be used to search out the emotional traces of videos. In this paper, we tend to gift our approach in instantaneously detecting the emotions of video viewers' emotions from electroencephalogram (EEG) signals and facial expressions. A group of emotion inducing videos were shown to participants whereas their facial expressions and physiological responses were recorded. The expressed valence (negative to positive emotions) within the videos of participants' faces were annotated by 5 annotators. The stimuli videos were also continuously annotated on valence and arousal dimensions. Long-short-term-memory recurrent neural networks (LSTM-RNN) and continuous conditional random fields (CCRF) were utilised in detecting emotions automatically and continuously. We tend to found the results from facial expressions to be superior to the results from EEG signals. We analyzed the impact of the contamination of facial muscle activities on EEG signals and found that most of the emotionally valuable content in EEG options are as a results of this contamination. But, our statistical analysis showed that EEG signals still carry complementary information in presence of facial expressions.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : A Novel Dynamic Model Capturing Spatial and Temporal Patterns for Facial Expression Analysis ABSTRACT: Incorporating spatial and temporal patterns present in facial behavior should substantially improve facial
PROJECT TITLE : Reviewer Credibility and Sentiment Analysis Based User Profile Modelling for Online Product Recommendation ABSTRACT: Even for humans, deciphering user buying preferences, likes and dislikes is a difficult undertaking,
PROJECT TITLE : An efficient Android malware detection system based on method-level behavioral semantic analysis ABSTRACT: Every day, 12 000 new Android malware samples will be developed, according to a recent report. The efficient
PROJECT TITLE : Development and Assessment of a New Global Mammographic Image Feature Analysis Scheme to Predict Likelihood of Malignant Cases ABSTRACT: Researchers in this project hope to create and test a new computer-aided
PROJECT TITLE : Automatic Land Cover Reconstruction From Historical Aerial Images An Evaluation of Features Extraction and Classification Algorithms ABSTRACT: As large-scale epidemiological studies including retrospective study

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry