Brain Signals Mobile App for Paralyzed Person

Project Title

Brain Signals Mobile App for Paralyzed Person

Project Area of Specialization NeuroTechProject Summary

Brain-Computer Interface (BCI) technology was first developed as a tool to provide basic communication, such as spelling, without movement. By detecting specific patterns of activity in the brain, BCIs can get a general idea of which messages or commands a user wants to send. For example, a user might pay attention to a flickering icon on a monitor with the letter “A” to spell that letter, or imagine left hand movement to move a cursor, wheelchair, or humanoid robot to the left. BCIs might detect brain activity through sensors outside the head, such as an electrode cap that detects the Electroencephalogram (EEG) or sensors inside the head, such as Electrocorticography (ECoG) activity that is detected during neurosurgery. Brain-Computer Interfaces (BCI) allow for direct communication between a person’s brain and technical devices without the need for motor control. BCIs thus constitute a promising assistive technology device for people with severe motor impairment, e.g. due to neurodegenerative disease. Among many different applications, researchers suggested their use for wheelchair control, thus rendering BCIs of high value for people with severe paralysis who are not able to control a wheelchair by means of a joystick. Using those minds waves we can perform different action in this project we will control home appliances which will be controlled by Patient and a caretaker Mobile App which receive notifications sent from patient. The patient will send brain waves and caretaker app will receive it as notifications that patient needs attention.

Project Objectives

The specific objectives are:

1. To design a Brain Computer Interface to interact physical environment for physically impaired people.
2. To acquire and process the EEG signal from non-invasive BCI (Neurosky Mind wave) device using Raspberry Pi.
3. To analyse the EEG signal in term of attention and meditation level by using their peak and average value.

Project Implementation Method

BCI system consists of a Neurosky headset connected to a computer. Neurosky sensors supply information to the computer. The computer runs the signal processing and classification algorithms and is connected to a microcontroller that controls the connected electronics devices or generate notification for monile app. The mobile app will receive signals and generate notification according to received signal type which will be received from EEG headsend to microcontroller and microcontroller to mobile. A BCI based control system is usually composed of five main units: signal acquisition unit, signal pre-processing unit, feature extraction unit, classification unit, and action unit that controls home appliences and generate mobile notifications. In signal acquisition block, the EEG signals are captured using the Neurosky Headset. Neurosky is an EEG headset which supplies 14-channel EEG data and 2 gyros for 2-dimensional controls. Its features are adequate for a useful BCI (Resolution and Bandwidth). Our system uses upper face gestures for actuation commands since most Neurosky sensors are located in the frontal cortex, they are the most reliable signals to detect. The EEG input signals are sent to the signal pre-processing unit for filtering and scaling and sent to the feature extraction block. In this block, the basic features are extracted and sent to the classification system. The classification block processes the input signals and outputs the control instructions. Later, these control instructions are sent to the microcontroller and mobile.

Benefits of the Project

So far BCIs have been conceived primarily as a solution for medical pathologies. However, it is possible to see BCIs more expansively as a platform for cognitive enhancement and human-machine collaboration. The BCI functionality of typing on a keyboard with your mind suggests the possibility of having an always-on brain-Internet connection. Consider what the world might be like if each individual had a live 24/7 brain connection to the Internet. Just as cell phones connected individual people to communications networks, BCIs might similarly connect individual brains to communications networks.

• The scope of Brain Computer Interface and Physical Interaction is very vast paralysed people can send notification to the caretaker without talking or doing anything physically they just have to think once and the notification will be sent to the caretake app it is that simple.
• We can also deploy this project for the kids who cannot talk and how this going to work is the phenomenon is same a headset is used to get the signal from brain and send those signals to the device processing the signals in to actions or may be a mobile to generate a notification for the parents.

Technical Details of Final Deliverable

1. Hardware Requirement:

Hardware requirements for the proposed system:

• Emotiv Headset
• Raspberry Pi 4
• Relay module

2. Software/Tools Requirement:

Software requirements for the proposed system:

1. Visual Studio
2. Linux OS/Windows OS
3. Raspberry Pi Software (IDE)
4. PyCharm
5. Microsoft Office + Visio + Project

3. Proposed Implementation Language(s):

Language requirements for the proposed system:

1. Python where we can, C++ where we must.
2. Swift and Kotlin for Mobile App development.
3. MongoDB.js, Express.js, React.js, Node.js for Web interface.

Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Medical , Health Core Technology NeuroTechOther Technologies Artificial Intelligence(AI), Internet of Things (IoT), Wearables and ImplantablesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	69616
EEG Emotiv Headset	Equipment	1	53746	53746
Raspbarry Pi 4	Equipment	1	8470	8470
Realy Module	Equipment	2	2200	4400
Internet Device	Miscellaneous	1	3000	3000