Brain control wheelchair using electric wave spectrum

Project Title

Brain control wheelchair using electric wave spectrum

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

The brain-computer interface (BCI) is a direct neural interface between a human brain and an external world. The electric wave (Electroencephalography) based wheelchair system is the major application of brain-computer interface (BCI) which allows immobile individuals to carry out their routine activities. To provide quality life to elders and the disabled, there is a need to design such a wheelchair that works smartly and offers easy maneuverability. Therefore, this paper proposes a model, that captures electric signals from the human brain and processes them to control movements of the wheelchair. The EEG method deploys an electrode that is positioned on a person’s head for the acquisition of an EEG signal. The Human brain has millions of interconnected neurons and patterns that are delineated as different feelings and emotions in the human body. These neurons produce synchronized electrical signals to generate brainwaves and can be detected by placing sensors on the scalp. These signals are imaged and then translated into movement commands by Arduino microcontroller which in return operates the wheelchair. In this system, an ultrasonic sensor HCSR-04 is also used for security purposes that will detect an obstacle around a wheelchair.

Project Objectives

1. To plan a Brain-Computer Interface based wheelchair for truly disarranged individuals.

2. To cycle the EEG signal from a non-intrusive BCI (Neurosky Mind wave) gadget utilizing Arduino Software.

3. To examine the EEG signal in terms of complete consideration and contemplation levels by utilizing their pinnacle and normal qualities.

Project Implementation Method

The main purpose of this project is to make use of parameters collected by Neurosky Mind wave Mobile Headset to drive the wheelchair according to the user’s command. Therefore, its methodology engages wheelchair to locomote around by using Brain signals. The block diagram Fig 1. Is explained below:

1. Signal Processing Technique:

This technique and device gathers and processes the brain signals produced by Neuro cells in the human brain. In our project, we are more focused to use a Non-invasive acquisition approach. This technique takes electrophysiological signals from the human head and evaluates them. The electroencephalogram (EEG) is usually utilized as it is simpler to implement and easy to use with the requirements for the BCI system. Therefore, we decided to use an electroencephalogram as the signal capturing technology.

1. Feature Extraction:

Since the electric signals are continuously being gathered by electrodes attached to the head, it is difficult to identify them without discrepancy; therefore, we classify them into the following few frequency categories. The motion of the wheelchair depends upon SNR four frequency ranges of the electrical signal of the brain. Different range of frequencies generates different control signals to steering a wheelchair in one of the four directions (7 Hz -8Hz left; 11 Hz -12 Hz right, 9 Hz-10Hz forward, and 13 Hz -14Hz reverse).

1. Application Interface:

1. Linking Neurosky Headset with BCI:

The Neurosky headset is generally used to record EEG waves. This gadget measures electrical signals and tracks brain activities. A (BCI) is an immediate method to convey between the cerebrum and an outer gadget. The electric signals collected from the EEG headset would then be delivered to BCI.

1. Interfacing BCI to Arduino Microcontroller:

The brain-computer interface then processes the input gained from the EEG headset. It then, interfaces with Arduino micro-controller.

1. Sending Signals from Arduino to Wheelchair:

The Arduino microcontroller will be encoded using its proper coding language to transmit the BCI output. It then moves the wheelchair forward, reverses the left or right direction according to the commands of the user. An ultrasonic sensor-based safety system is also ported with the controller to make the wheelchair safe and secure for the user.

Figure 1. Working principle of Brain-controlled

Wheelchair

1. A wheelchair System:

The following is a block diagram of the wheelchair control system based on the brain wave spectrum of the EEG sensor (Electroencephalogram). The EEG Sensor captured the brain activity. This signal is monitored on the laptop via Bluetooth and then signals interfacing with Arduino through a laptop. Arduino decides by getting instructions through EEG sensor and ultrasonic sensor and sent these instructions to DC motor for movement of the wheelchair

            Figure: 2 Proposed wheelchair system

Benefits of the Project

This project is dedicated to the disabled and elders. They imagine these motions and the wheelchair takes them in those directions. That's the simple stuff.

The self-driven feature enables the wheelchair to move by itself and go around small obstacles.

Choosing an old wheelchair and make it smart and functional again by adding different sensors and a footrest.

Technical Details of Final Deliverable

With the Brain-computer Interface (BCI) people with disabilities can certainly control their own wheelchairs through the electrical signal of brain waves. There are several methods available to record electrical signals corresponding to some type of mental response of any human. Here, Electroencephalography (EEG) is used for the recordings of the brain’s electrical neural activity and also recording the electrical signals from the brain and signal differ from person to person. The greatest advantage of EEG signals is that the complex pattern of neural activity can be recorded in a split second after the stimulus is given. The electrodes of an EEG device capture electrical activity expressed in various EEG frequencies. Using an algorithm called a fast Fourier transforms, these raw EEG signals can be identified as distinct waves with different frequencies. The required signal of left, right, upward, and downward can be identified by using software Neuro sky driver that using the algorithm of FFT.

The HC-05 Bluetooth module is a communication tool that solely operates in two modes. The order response operation and automatic connection operation. When the Bluetooth module switches to automatic mode, it follows the lastly set path to transmit the data automatically while in order responsive operation mode, user can send the AT command to Bluetooth module to preset the controlling parameters and transmit control order. The operational modes can be selected by switching the input from PIN11.

The microcontroller Arduino (UNO) works based on the AT-mega-328 datasheet. It consists of 14 input and output ports. Out of which 6 pins can be used as outputs and analog inputs, a 16MHz resonator Power supply, USB Jack, an ICSP header, accordingly. Selection of this microcontroller is done based on the required connection to DC motors and Bluetooth module.

Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther Industries IT , Medical Core Technology NeuroTechOther Technologies Artificial Intelligence(AI), Internet of Things (IoT)Sustainable Development Goals Good Health and Well-Being for People, Industry, Innovation and Infrastructure, Life on LandRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	60800
Wheel Chair	Equipment	1	9000	9000
Neurosky MindWave Headset	Equipment	1	30000	30000
UNO Arduino	Equipment	2	800	1600
Ultrasonic Sensor	Equipment	4	300	1200
Bluetooth Module	Equipment	2	500	1000
DC Motors	Equipment	4	2000	8000
Printing and Other	Miscellaneous	1	10000	10000