With the evolution of technology, its interaction with humans has become easier day by day. After touchscreen and voice-controlled systems, the world is moving towards brain-controlled systems. Nevertheless, the touch screen and voice-controlled systems show an effective contribution to the
BrainKey
With the evolution of technology, its interaction with humans has become easier day by day. After touchscreen and voice-controlled systems, the world is moving towards brain-controlled systems. Nevertheless, the touch screen and voice-controlled systems show an effective contribution to the community. However, for disable persons (for instance, dumb persons), still, these systems are useless. Thus, to overcome such limitations, this project aims to develop an on-screen brain-controlled keyboard. The system will be based on Brain-Computer Interface (BCI) technology which utilizes Steady-State Visual Evoked Potential (SSVEP) to allow a user to type by looking at flickering square boxes containing character keys. Signal processing and Machine Learning techniques will be utilized to process and classify the brain signals. Furthermore, to speed up the typing process, Natural Language Processing (NLP) will be used to predict the spelling instead of typing the whole spelling. It is believed that the proposed work will serve paralyzed people by enabling them to enter the data on personal computers without any external physical assistance.
The basic purpose of this project is to create a system that enables humans to interact with technology using the brain instead of any physical efforts.
The focus of this project would be to get input by exploiting the SSVEP signals which generate brain wave patterns according to visual flickering at a particular frequency. The generated brain signal has almost the same frequency as that of the visual stimulus.
Preparing a dataset of at least 5 people.
Feature extraction of the dataset.
Feature classification of the dataset.
Creating an on-screen keyboard UI that will partition the keyboard in different flickering frequencies.
Creating the desktop application to process signals from the headset and convert them into commands.
Merging both UI and signal processing applications and adding NLP for increased typing speed.
Even though touch screens and voice-controlled systems have revolutionized the interaction of humans with modern technology, there are still some people who are unable to use these systems. People who are fully physically paralyzed who can only see through their eyes but are unable to do any physical movement. E.g Amyotrophic Lateral Sclero, spinal cord injury, etc.
This project is focused on creating a system that will enable people, with earlier discussed conditions, to interact with different technologies. Just by using their eyes and brain to interact with technology, without doing any physical efforts.
The final deliverable product will contain,
A headset that will enable us to receive signals from our brain and send them to the computer.
A desktop application
That will show the partitioned on-screen keyboard. Each partition flickers at a different frequency. User focusing on a particular partition will result in brain producing signals according to the frequency of partition.
The application will also process the signals received from the headset and convert them into commands and type the required character.
The application will also have the support of Natural Language Processing (NLP) to speed up the process of typing by predicting the word user want to type from earlier typed characters.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Emotiv Insight Headset | Equipment | 1 | 49000 | 49000 |
| Bluetooth module (HC-05) | Equipment | 1 | 15000 | 15000 |
| Project Report Printing and Binding | Miscellaneous | 1 | 4000 | 4000 |
| Total in (Rs) | 68000 |
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