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This Paper starts an innovative idea to design an automatic wheelchair for people who is physically challenged.These automatic wheelchairs are controlled by brain waves of the persons to wherever they want to go without others help. The entire system is controlled with the help of advanced microcontrollers and digital signal processors. The signals are taken out from the human brain with the help of electroencephalography technique.This system performs the operations as same as of a wheelchair which is operated with a man help.
This system is very much helpful for people who is lost their legs and hands in accidents, and who are amputators (who has lost the function of legs and hands by birth).This system provides sensors which gives safety traveling for them. They also take their systems to travel anywhere without any obstacles in their path without anybody help.
The proposed system is feasible for the real time environment with the currently available technology and very useful for the people who are physically challenged to lead their life in a successful manner. This system is very effective than automatic wheelchairs using sensors both in cost and also in performance.
A brain-computer interface (BCI), sometimes called a direct neural interface or a brain- machine interface, is a direct communication pathway between a human or animal brain and an external device. In this definition, the word brain means the brain or nervous system of an organic life form rather than the mind. Computer means any processing or computational device, from simple circuits to the complex microprocessors and microcontrollers.
An interesting question for the development of a BCI is how to handle two learning systems: The machine should learn to discriminate between different patterns of brain activity as accurate as possible and the user of the BCI should learn to perform different mental tasks in order to produce distinct brain signals. BCI research makes high demands on the system and software used.
Parameter extraction, pattern recognition and classification are the main tasks to be performed in a brain signals. It is assumed that the user of this system has no both legs and hands or legs but their brain is active as like as of a normal man. This system gives a full freedom and control of their actions by their own thought. The system uses adequate tools to lead a safety path for them. Their brain thoughts are preprogrammed according to their thoughts using a BMI interface.
The Electrical activity emanating from the brain is displayed in the form of brainwaves. There are four categories of these brainwaves ranging from the most activity to the least activity. When the brain is aroused and actively engaged in mental activities, it generates beta waves. These beta waves are of relatively low amplitude, and are the fastest of the four different brainwaves. The frequency of beta waves ranges from 15 to 40 cycles a second next brainwave category in order of frequency is Alpha. Where beta represented arousal, alpha represents non-arousal. Alpha brainwaves are slower and higher in amplitude. Their frequency ranges from 9 to 14 cycles per second. The next state, theta brainwaves, is typically of even greater amplitude and slower frequency. This frequency range is normally between 5 and 8 cycles a second. A person who has taken time off from a task and begins to daydream is often in a theta brainwave state. The final brainwave state is delta. Here the brainwaves are of the greatest amplitude and slowest frequency. They typically center on a range of 1.5 to 4 cycles per second. They never go down to zero because that would mean that you were brain dead. But, deep dreamless sleep would take you down to the lowest frequency. Typically, 2 to 3 cycles a second.
Fig 1: Different Types of Brain Waves
The same four brainwave states are common to the human species. Men, women and children of all ages experience the same characteristic brainwaves. They are consistent across cultures and country boundaries. In the proposed system it is assumed that the users experience alpha or beta waves oftenly and theta waves rarely. In the proposed system depending upon their thoughts different waves are experienced with different frequency and amplitude.
Fig2 : General Block Diagram of the Proposed System
Fig 2 shows the general block diagram of the proposed system. Electrode cap is placed in the scalp of the person. The signals taken out from the human brain will be in the range of mV and µV. Hence they are fed to an amplifier. Then it is sent to a Analog to Digital Converter to convert the analog brain signals in to digital form. Then it is sent to a signal processor where parameter extraction, pattern classification and pattern identification are done. These digital signals are fed as input to microcontroller unit. In the microcontroller unit there are two more devices are. They are stepper motors and sensors .
Fig 3 shows a person wearing an electrode cap. These electrode caps contains electrodes which are placed on the skull in an arrangement called 10-20 system, a placement scheme devised by the international federation of societies of EEG. In most applications 19 electrodes are placed in the scalp. Additional electrodes can be added to the standard set-up when a clinical or research application demands increased spatial resolution for a particular area of the brain. High-density arrays (typically via cap or net) can contain up to 256 electrodes more-or-less evenly spaced around the scalp. The main function of the electrode cap is to take the brain signals in the form of electrical signals. The signals taken out from the Electrode cap are fed to an amplifier. A sensor is being placed nearby the electrode cap to observe the actions of electrode cap. Incase the electrode cap fails or any emergency stop the system has been stopped by just the user buffing his/her cheeks.
Fig 3: A person wearing Fig 4:Placement of electrodes in 10-20
electrode cap system
The output signal from the electrode cap will be in the range of mV and µV. So, these signals will not be suitable for signal processing. Hence these signals are fed to an amplifier. Each electrode is connected to one input of a differential amplifier (one amplifier per pair of electrodes); a common system reference electrode is connected to the other input of each differential amplifier. These amplifiers amplify the voltage between the active electrode and the reference (typically 1,000-100,000 times, or 60-100 dB of voltage gain).
ANALOG TO DIGITAL CONVERTER:
The output signals from the amplifier are analog in nature. They also contain some unwanted signals. Hence the output signals are filtered using high pass and low pass filters. The high-pass filter typically filters out slow artifact whereas the low-pass filter filters out high-frequency artifacts. After the signal is filtered they cannot be directly fed to a digital signal processors and microcontroller unit as they are in analog form. Hence these signals are sent to an Analog to Digital converter to convert the incoming analog signals in to digital signals.
Using the output signal from the A/D converter, parameter extraction, pattern classification and pattern identification are done. Then the signals are fed to a Fast Fourier Transform Unit. This is done to simplify the calculations. An FFT algorithm computes the result in O (N log N) operations instead of O (N2) operations. The output signals from the signal processor are fed to a Microcontroller unit.
The output signals from the signal processor are fed to a microcontroller unit. This microcontroller unit performs the robotic operation with the help of a stepper motor. It will control the operations such as turning the wheels right, left and straight of the road depending upon the input signal. For different patterns of input signals it will be pre-programmed to do a specific operation. The reference signal will be already stored in the microcontroller memory in digital form. Usually an 8 bit or a 16 bit microcontroller is preferred depending upon the number of operations to be performed. The complexity of the microcontroller programming increases with the number of operations which has to be performed. An image sensor is used to image the path whether an obstacles occurring or not. If an obstacle occurs then it enables the horn and a 'BEEP' occurs.
Two stepper motors are used in each wheel which is interfaced with microcontroller. From the microcontroller output the stepper motors rotate backward, forward, left and right directions.
Sensors are used in the circuit which senses the object on the road which crosses while they are traveling. These sensors enable the microcontroller to produce a control signal to alert the persons who crossing over them by a beep sound. Another sensor is used near the electrode cap to watch the activity of the electrode cap.
WORKING OF THE PROPOSED SYSTEM:
For every human activity the brain waves changes its pattern. For example, if a person moves his/her legs or hands a specific brain wave pattern is obtained. If he thinks to go anywhere or to turn his/her path right or left a specific pattern of brain waves are produced. These brain waves normally control man's every action. If he wants to move then brain sent specific information to the legs to do the operation. So the same type of brain wave is produced if he/she doesn't have legs and hands. But the operation of going anywhere will not be performed due to the absence of working of legs and hands. So, just by thinking of moving to anywhere, a brain wave which is capable of performing a specific operation is generated in the brain. Due to the lack of the function of their nervous system of hands and legs or the entire body nervous system except the brain they didn't move anywhere without the help of others
In the proposed system, the brain waves are pre-recorded for each operation to be performed and these waves are used as reference signals. These signals are stored in the microcontroller memory. For each reference signal in the microcontroller memory the system is preprogrammed to do a specific operation. Depending upon the reference signal in the microcontroller memory the stepper motors are interfaced with microcontroller to do specific operation. The sensors are used to view any obstacles may occur during the working. If any obstacles may occur while traveling on the road they enable horn to alert the opponents who cross on the road.
For example let us say a person, who has no function of legs and hands, is thinking of to go to a nearest place (to start the vehicle initially) a brain wave is produced. This brain wave is observed, processed, converted into digital signal and then sent to microcontroller memory. In the microcontroller memory it is compared with the reference signal and if it is matched the pre programmed operation is done for that particular signal, i.e, the system is started. Like this the turning of wheelchair towards right, left, forward, backward and reverse operations are done with the help of reference signals, brain produced control signals and preprogrammed operations.
Two sensors are used. One is to watch the actions of electrode cap. When it is not functioning it provides the emergency stop of the system and it alerts the user by an emergency alarm. Another is an image sensor. It views each and every objects crossing and enables the horn only if it is an obstacle. Usually a stepper motor controlled system is used for this purpose.
This system is very user friendly and the system can be designed according to the user's requirements i.e. the number of operations required for the user can be fixed by him and the system can be designed accordingly. So the number of operations that has to be performed by the system can be increased or decreased and the complexity of the design varies accordingly. Thus the system is versatile. This system is hundred percent feasible in the real time environment and it can be implanted to any human irrespective of their age. This system is very much useful for the people who has been attacked by polio and lasting their hands and legs. Fig 5,6,7,8 shows an example of wheelchairs.
These wheelchairs are powered by two small lithium-ion batteries which have to be charged once in 2 day. Lithium-ion batteries have very high charge density (i.e. a light battery will store a lot of energy). They are of ultra-slim design and hence they occupy very less space. Moreover their life time will be longer when compared to other batteries. Hence they are preferred when compared to other batteries
Fig. 5.automatic wheelchair fig. 6.a man in chair with
Fig...7. A man in chair fig. 8.automatic wheelchair
Difference between automatic wheelchairs and brain controlled automatic wheelchairs
Brain controlled automatic wheelchair
1. Ease of construction
Complex in construction
2. User can full control over the system
User cannot have full control over the system
3. Semi automatic
4. Requires simple control unit
Requires complex control unit
5. Cost is very low
Cost is high due to complex circuits
In the recent development in technology this system gives the reality in life to the people who have no function on legs and hands. The performance of the proposed system will be better than the existing artificial wheelchairs as the user has full control over the Brain Controlled wheelchairs. The built-in battery lasts anywhere from 25 to 40 hours so it can support a full day's activity.
The cost of the proposed system is very less when compared to existing
ones. So middle class people who cannot purchase the existing one can purchase this system. This system will be very useful in India generally for the people who lost their function of both legs and hands in polio. This idea can be made them for an ideal society.