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 mig
Brain Signals Mobile App for Paralyzed Person
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.
The specific objectives are:
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.
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.
1. Hardware Requirement:
Hardware requirements for the proposed system:
2. Software/Tools Requirement:
Software requirements for the proposed system:
3. Proposed Implementation Language(s):
Language requirements for the proposed system:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 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 |
| Total in (Rs) | 69616 |
Stock Market is one of the most important pivots of countries economy. For the growth...
The reason we chose this project is that we live in a modern era where deep fake innovatio...
We aim at designing a small, safe and smart locomotive for transportation inside organizat...
Visually impaired and completely blind people face constant challenges and issues in their...
Robots are generally used to make human life easier. From time to time technology come up...