Sizz Arians

7/31/2019 Sizz Arians

1/10

By,

Ramya C S (10LEE02)

Sakthivel A (10LEE03)

Gayathri N (10LEE05)

Kangaraju P (10LEE09)


2/10

OBJECTIVE

21 million people in India

2.1% of the total population

Immobility totals to 61,05,477

Unable to execute their daily chores

Develop a prosthetic model

Utilises the brain signals to activate

Replace the impaired part

Model a cost effective solution


3/10

EXISTING TECHNIQUES

A testing of brain activated prosthetic hand used to pick

a cup was done at a cost of Rs.5,00,000 in US

Testing of neuron activated daily chores is performed and

research is carried on to improve it

A lower extremity prosthesis (leg) can minimum cost to

Rs.2,90,000

An upper extremity device (arm) can range from

Rs.1,34,000


4/10

BCI &UNITS OF PROJECT

Brain Computing Interface (BCI) :System able to detect and interpret the mental activity

Changes it to computer interpretable signals

Activities completed without using muscular movementUnits of project:

Brain signal capturing unit

Signal processing unitController unit

Actuator and hand unit


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BASIC CONCEPTS OF EEG CAPTURING

Brain signals are of Delta, Theta,Alpha, Beta and Gama form

Application of DCT and

Butterworth filtersOriginal signal is multiplied with

window function and transform is

computed for each segmentSize of wavelet depends on

frequency components used in the

series

EEG CAPTURING

NORMALISATIO

N

SEGMENT DETECTION

FEATURE

EXTRACTION

CLASSIFIER

EEG

OUTPUT


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BLOCK DIAGRAMBRAIN

ELECTRODES (EEG)

SIGNAL

S

STORAG

E

ENERGISE

ACTUATO

R UNITS

SIGNAL TOCONTROLLER

UNIT

SIGNAL

COMPOSING

UNIT

FINAL

THOUG

HT

PROGRAMSELECTION

BASED ON

SIGNAL

PATTERN

WAIT TILLMOVEMENT

IS

COMPLETED

SIGNALS

SIGNALCOMPOSING

UNIT

CHECK

FOR

MATCHIN

G

AA


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SIGNAL CONDITIONING UNIT

Signals are captured using EEG capSignals filtered to eliminate noises and

other signals

To improve the signal qualityconditioning is done

Patternisation is done to segregate the

signals based on the output to beinitiated

Patternised data is compressed to

provide minimum storage area

EEG SIGNAL

FROM BRAIN

CONDITIONING

PATTERNISE

COMPRESSION

CONDITIONED

BRAIN SIGNAL

FILTERING


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SCHEDULE OF WORKJune : Selection of topic and basic feasibility of project was

analyzed

July : Theoretical study of the project

August : Software simulation of the project

September : Designing of artificial hand

October : Testing the working of hand

December : Real time brain signals capturing and its

processing

January : Integrating brain signals and artificial hand

February : Testing and debugging the project

March : Final makeover of the project and report formulation


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CONCLUSION

The various project development techniques and study of

the existing methodology of the project has been done. The

theoretical concepts related to the project has beencollected. A software necessary for processing the brain

signals has been studied and work is to be proceeded by

analyzing the brain signal data set using the software andfilters for segregating thoughts are to be designed and

constructed.


10/10

REFERENCES

Onur Varol, Mustek Erhan Yalim, Ram EEG dataclassification and applications using SVM, Istanbul

Technical University, 2010

Wenjie Xu, Cuntai Guan, High accuracy classification

of EEG signals , Jiankang Wu-Institute of Infocomm

Research

Lebang Due, Mohd Syaifuddin, Designingand degrees

of freedom humanoid roboticarm

www.bci2000.org

Documents

Sizz Arians