Ppt Tnscst

PROSTHETIC ARM FOR PARALYZED PEOPLE

P.S.R.ENGINEERING COLLEGESIVAKASI

GUIDED BY PRESENTED BY

Mrs.A.PADMA [AP/CSE] G.PARVATHY D.RENUKA DEVI

OBJECTIVE

The main aim of our project is to fulfill the

basic needs of paralyzed people by

themselves without depending on others.

Paralysis is most often caused due to some fatal accidents and due to some diseases like stroke, trauma and multiple sclerosis etc.,

SCOPE OF THE PROJECT

The scope of our project is to convert the thoughts of paralyzed people into actions by simulation.

(Thoughts are converted into signals by fitting electrodes inside the brain, the electrodes will convert the thoughts into four types of EEG signals namely Alpha, Beta, Delta, Theta. Among these EEG signals Beta signal is associated with thinking)

Contd…

Beta signal associated with thinking is chosen as an input to our project.

Beta signal is generated in MATLAB, and is loaded into the wavelet toolbox for analyzing process.

Contd…

In the analyzing process the input signal is splitted into various type of signal.

The coefficients of the analyzed signal is saved and converted into binary values.

These binary values are then given as input to the Back Propagation Network, which will produce the final output.

EXISTING SYSTEM

The previous implementation makes use of many hardware equipments.

Also the existing system was implemented using animals like monkeys, but at present only they are trying for human beings.

PROPOSED SYSTEM

Our project is more useful for the paralyzed people.

The paralyzed people can do their day-to-day activities by themselves.

HARDWARE REQUIREMENTS

Processor : Pentium IV

Main Memory : 256 MB

Hard Disk Drive : 80 GB

SOFTWARE REQUIREMENTS

Plat Form : Windows XP/2000

Front End : MATLAB (version 7)

The modules of our project includes,

Conversion of Thoughts to Signals.

Conversion of signals to Binary data.

Training and Testing BPN Network.

MODULES

CONVERSION OF THOUGHTS TO SIGNALS

The Beta signal associated with thinking is generated using the sin function in MATLAB.

The signal is then loaded into the wavelet tool box and is analyzed.

The coefficients of analyzed signal is stored in workspace window.

CONVERSION OF SIGNALS TO BINARY DATA

The analyzed coefficients are loaded and converted into binary data using zeros and ones function.

zeros - Create an array of all 0’s ones - Create an array of all 1’s

BPN Architecture

TRAINING AND TESTING BPN NETWORK

The Back propagation network is initially trained by giving different input with the frequency range [13-30HZ].

The network is then tested by giving the same and different frequencies as in the training process.

If the testing input is in the range [13-30HZ] then the output will be one (i.e., there is arm movement) else the output will be zero (i.e., there is no arm movement).

CONCLUSIONThus our project will be more useful for the paralyzed people.

They can perform their day-to-day activities like drinking water, dressing, eating by themselves without depending on others.

Even they can operate a computer and play games.

REFERENCES

Laurene Fausett “Fundamentals of Neural Networks Architectures, Algorithms, and applications”.

Arumugam “Biomedical Instrumentation”.

Stephen J. Chapman “MATLAB Programming for Engineers”.

www. mathworks.com