synchronization and analysis of olfaction enhanced multimedia

The user quality of experience (QoE) can be enhanced by enriching an audio-visual multimedia content with multiple sensorial components. Traditional multimedia engages two human senses i.e., vision and auditory. Olfaction enhanced multimedia (OEM) is generated by adding an olfactory effect in tradit

Project Title

synchronization and analysis of olfaction enhanced multimedia

Project Area of Specialization

Augmented and Virtual Reality

Project Summary

The user quality of experience (QoE) can be enhanced by enriching an audio-visual multimedia content with multiple sensorial components. Traditional multimedia engages two human senses i.e., vision and auditory. Olfaction enhanced multimedia (OEM) is generated by adding an olfactory effect in traditional multimedia content. In this project, OEM is generated by synchronizing olfaction dispenser with traditional multimedia content. Both the traditional and OEM content are displayed to users and their brain activity is recorded by using commercially available EEG headset. Human brain activity is analyzed in response to both the OEM and traditional multimedia content.

Project Objectives

The main aim of this project to analyze human brain activity in response to OEM and traditional multimedia content. The objective set for this project is

1. Design of olfaction dispenser
2. Synchronization of olfaction dispenser with traditional multimedia content
3. EEG data acquisition of different subjects in response to OEM and traditional multimedia content.
4. Analysis of brain activity using recorded EEG signals

Project Implementation Method

Data Acqusition

It is the process in which we measure physical condition of real objects and then convert them into digital values that can be computed by a computer. Data acquisition systems (DAS), basically transform analog signals into digital.

Preprocessing

After data acquisition there is another step which plays an important role in analysis i.e. data pre-processing. During the data acquisition there many factors which can affect our data like noises, sensors etc. In this process we have to remove these noises or false data which can affect our analysis. Furthermore, we have to perform different transformation and feature extraction techniques etc. The output of data preprocessing will be our final training dataset.

Feature Extraction

Feature extraction strategy has a vital role in processing of the signals and they are enhancing day by day. Fourier transform and deep learning algorithms can be used to extract features. There are many online tools available through which you can extract features and can extract more accurate results. Brain signals are transformed to some values and then characterized these qualities easily by using classification methods and after that convert to directions by using machine learning. We can extract features from EEG signals by using two various domains like time and frequency domain features (TDF), (FDF) .

Classification

Emotions are discrete and fundamentally different constructs. Researchers conclude that humans have some basic emotions and they are distinguishable by an individual’s facial expression and biological processes.

Benefits of the Project

It will help in research in medical field.

A product will be launched to release stress.

Technical Details of Final Deliverable

Following are the deliverable of our project:

1. Olfaction dispenser product.
2. Emotion recognition with synchronization of olfaction enhanced multimedia.

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

Medical , Health

Technologies

Augmented & Virtual Reality

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com