Brain Controlled Robotic Car using Raspberry Pi
₹25,238.00
Brain Controlled Robotworks under the principle of BCI- Brain Computer Interface which you can control the Robot using your Brain Waves – EEG using Brainsense / Mindwave Mobile with Raspberry Pi 3
Features:
Analyzing Brain waves | Controlling Robotic Car
Shipping : 4 to 8 working days from the Date of purchase
Package Includes:
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Complete Hardware Kit
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Demo Video-Embedded Below
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Abstract
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Reference Paper
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PPT (20 Slides)
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100 in stock
Description
Abstract
In our society there are more people suffered by paralytic diseases causes them several disabilities like they are unable to talk and unable to move physically and unable to express their everyday basic needs, but they can still use their eyes and sometimes move their heads. This Project is working under the principle of Brain-Computer Interface (BCI)
Our model helps them to control the wheelchair to the desired place by their eye blink. So they don’t need any caretaker to drive them, they can drive their wheelchair themselves. Wheelchair starts moving when we run the program, then the direction is chosen by having eye blinks.
Introduction
The Brain-Computer Interface (BCI) is one of the communication channel used to make an interaction between the human brain and a digital computer. BCI which monitors EEG waves from the Brain. EEG –Electroencephalography which monitors an Electrical property of the Brain along with the Scalp (Noninvasive). The Neurosky Mindwave mobile measures intentionally directed EMG activity (blink strength).
The Raspberry Pi is a credit card sized single computer or SoC uses ARM1176JZF-S core. SoC, or System on a Chip, is a method of placing all necessary electronics for running a computer on a single chip. Raspberry Pi needs an Operating system to start up. In the aim of cost reduction, the Raspberry Pi omits any onboard non-volatile memory used to store the bootloaders, Linux Kernels and file systems as seen in more traditional embedded systems. Rather, an SD/MMC card slot is provided for this purpose. After boot load, as per the application program, Raspberry Pi will get executed.
Existing System
In the existing system, every application is developed using Matlab, it requires a computer for processing signal and processing application through Matlab.
Proposed System
Since the system uses Raspberry Pi, it does not require Matlab for processing the signal. Raspberry pi which has in built Bluetooth, so that there is no need of external Bluetooth. Wheel chair start moving automatically, when the system ON, then by having one blink, wheel chair will turn left and when two blink is detected , the car turns right. If it detects abnormal blink, wheel chair stops automatically.
Demo Video
Block Diagram
Block diagram Description
Robotic Car is connected with GPIO pins of Raspberry Pi, which contains inbuilt Bluetooth. Mindwave mobile or BrainSense which also has inbuilt Bluetooth, is connected with Raspberry Pi.
Circuit Diagram
Project Description
In this system, Raspberry Pi acts as a core, which these applications don’t require any laptop/pc with Matlab. Since it is mini Pc, it will process the signal by own. When the system begins to run, wheelchair moves automatically, whenever one blink is detected car turns left, if two blink is detected car turns right. If any abnormal blink is detected car stops automatically. Since Raspberry Pi is having inbuilt Bluetooth, it doesn’t requires any external Bluetooth for any application. Main application of this system is for paralyzed people, by this system they can able to move their wheelchair, without any dependencies.
Hardware Required
- Raspberry Pi
- Mindwave mobile or Brain sense
- Robot chassis (Motor, Driver IC)
- Batteries
Software Required
- Raspbian OS
- SD card Formatter
- Win32 disk imager
Conclusion
This system can be easily reconfigurable for other parameters like attention, meditation and adding a number of blinks for movement in further more directions. The intensity of Eyeblink differs for every human, we can reconfigure the code for high accuracy for blink detection.
Additional information
Weight | 0.000000 kg |
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