Feet with Rythm using EEG

Project Title

Feet with Rythm using EEG

Project Area of Specialization NeuroTechProject Summary

The Brain-Computer Interface (BCI) is a system that sends and receives signals and data based on the intensity of electrical signals using an Electroencephalograph (EEG) and a Digital Signal Processor (DSP). We will use the headset (EMOTIV EPOCX 14) in our research because it features 14 EEG channels and two reference channels for accurate spatial resolution. This device has a 14-electrode installation mechanism and samples at a rate of 128 samples per second using a sequential sampling method. We're working on a non-invasive BCI project that includes the development of the game "FEET WITH RHYTHM." The structure of BCI is made up of five components that form a closed loop. The terminology utilized is "control paradigm," "measurement," "processing," "prediction," and "application." BCI reads a user's intention or mental state and interprets it.

Project Objectives

The primary objective of our project is categorized into the following categories: Introduction Feet with Rhythm using EEG 5 1. Using BCI systems for navigation and control purposes by thoughts.

2. We will have one player, whose movements will be controlled by thoughts.

3. To move the player in the left, right, and forwarding direction.

4. To make the player ‘jump’ by thought. 5. To develop creativity and individuality.

Project Implementation Method

Signal Acquisition This step captures the brain signals, which may include noise reduction and distortion correction. Brain signals are recorded on the users' scalps using electrodes attached to an EEG cap. This is non-invasive, and the user is not harmed. To send data to the system, the user presses a button or uses a mouse in a standard interfaces way. BCI necessitates a "Control paradigm" that the user is in charge of. The user can imagine the movement of a body part or can concentrate on a particular object, to generate brain signals with the user’s purpose. Some BCI systems do not involve the user's deliberate efforts; instead, the device automatically detects the user’s mental and emotional states. These states are classified as active, reactive, or passive techniques from an interaction standpoint.

Preprocessing or Signal Enhancement The preprocessing stage converts the signals into a form that can be further processed. The detected signals are very faint, and even eye blinks have a significant impact on them. As a result, complicated algorithms are used to improve data quality to expose brain patterns. Invasive and non-invasive methods can be used to measure brain signals. EEG is a non-invasive approach. EEG is the most popular and promising in the use for BCI games.

Extraction of Features This stage identifies different and distinct information in the recorded brain signals. The signal is then mapped onto a vector including effective and discriminant features from the observed signals after being measured. The challenge of extracting this fascinating data is really difficult. Other signals from a finite number of brain processes that overlap in both time and place are blended with brain signals. Furthermore, the signal is rarely stationary and is susceptible to artifacts such as electromyography (EMG) or electrooculography (EOG).To reduce the complexity of the feature extraction stage while keeping essential information, the feature vector must also be of a low dimension.

Classification The feature vectors are used to classify the signals in the classification stage. To figure out the user’s intentions, effective pattern recognition requires the selection of Introduction Feet with Rhythm using EEG 4 good discriminative features. This stage determines the user's purpose or measures their emotional and mental state.

Control Interface When the user’s intention is recognized in the prediction step the output is used to adjust the application's environment. Finally, the user receives feedback on the program change. The control interface stage translates the classified signals into commands that be understood by any device connected with the system such as a wheelchair or computer.

Benefits of the Project

1. To play the game, just brain signals are required.

 2. Users must control their brain activity in order to generate signals that operate computers.

3. Human behavioral studies of BCI use.

4. BCI games have the potential to improve motivation and neurofeedback training results.

 5. Investments in BCI software and technology in the gaming business may help to stimulate the field and generate new devices with compelling settings.

Technical Details of Final Deliverable

This will be a desktop application based on AI and Neurotech. The app will process brain signals, which we will get through an EEG device (Emotive Epoc headset), and based on these signals, will make decisions and make the character of the game move in right or left direction, or jump.

Final Deliverable of the Project Software SystemCore Industry ITOther Industries Education Core Technology NeuroTechOther Technologies Artificial Intelligence(AI)Sustainable Development Goals Quality Education, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
EEG headset(NeuroSky)	Equipment	1	50000	50000
High and computing device	Equipment	1	20000	20000
printing	Miscellaneous	5	2000	10000