EARLY STROKE IDENTIFICATION USING MICROWAVE HELMET

Post on 18-Dec-2014

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This presentation gives a brief description about the stroke finder helmet which was developed recently by scientists. It describes about the main components in the stroke finder helmet and its advantages over the current diagnosis systems that we have now a days.

Transcript of EARLY STROKE IDENTIFICATION USING MICROWAVE HELMET

EARLY STROKE IDENTIFICATION USING MICRO WAVE

HELMET

BY, GUIDED BY,

CIJU VARGHESE ANJALI. R

S7 EC B ASST. PROF.

R.NO 10 EC DEPT.

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INTRODUCTION

Stroke is the No.3 cause of death. (#1 – Heart Disease, #2 – Cancer)

5 million people/year die and another 5 million are permanently disabled.

Every 3.1 minutes someone dies of a stroke.

Time is a crucial factor.

For neurologists “time is brain”.

Limitations of current diagnosis.

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WHAT IS STROKE ?????

Brain tissues are damaged from a sudden loss of blood flow, resulting in a loss of neurological function

Types: Ischemic stroke (85%) is blood flow is

blocked to the brain.Hemorrhagic Stroke (15%) is bleeding

occurs from vessels within the brain.

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CURE FOR STROKE

tPA (Tissue Plasminogen Activator)

is a clot-busting drug

It dissolves blood clots obstructing blood flow to the brain.

Medical Surgery

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WHY MICROWAVE DIAGNOSIS?

Microwave property of non-ionising radiations.

Zero side effects to body.

Relatively cheap,compact,portable technology.

Vast research and development in Microwave Tomography(MWT).

Exploits dielectric variations in brain.5

DIELECTRICS IN HUMAN BRAIN

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STROKE FINDER HELMET

Consists of:

A helmet-like antenna system which is placed on the patient’s head.

A microwave unit plus a computer for equipment control, data collection.

Signal Processing.

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ANTENNA SYSTEM

10 triangular patch antennas.

Power input is 1mW.

Frequency Range 0.3-3.0GHz

A liquid(water) bag is placed between antenna and skull.

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WORKING OF ANTENNA SYSTEM

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SIGNAL PROCESSING

Data from each channel is pre-processed.

The total output signal power is made equal.

Data is transformed by an algorithm.

Full reconstruction of dielectric parameters algorithm is used.

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RECONSTRUCTED IMAGE

PERFORMANCE ASSESSMENT

Specificity v/s Sensitivity is plotted.

Area under curve(AUC) should be between 0.5 and 1.

Better performance to detect ICH v/s healthy(AUC=0.88).

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FUTURE SCOPES

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CONCLUSION

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REFERENCES