Automatic Blood Pressure Measurement Finger Pulse Sensor and

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Automatic Blood Pressure Measurement

Finger Pulse Sensor and DSP Chip

EGR 1205 Poster

Presentation Day

March 2012

Abstract

Our main objective in this project is to create an automatic blood pressure device using a finger pulse sensor combined with a DSP processor.

Define the Problem

High blood pressure is the cause of hundreds of thousands of deaths every year and many people are not aware they have high blood pressure.

High blood pressure cause extra stress to be placed on the inner walls of arteries causing numerous health issues class3_slides.pdf, slide 2

Non-invasive automatic blood pressure devices can be used by everyday people in their own home.

Automatic blood pressure devices would allow for

Americans to monitor their blood pressure on a daily basis. source: http://upload.wikimedia.org/wikipedia/ commons/thumb/e/e5/Diagram_of_the_human_heart

Understanding the Problem

Blood pressure is broken down into two parts:

Systolic: higher number, measured when the ventricle tenses and forces blood out

Diastolic: lower number, measured when the ventricle relaxes and fills with blood

Blood pressure is measured through the brachial artery in the arm, right above the elbow.

EPA’ s

Class1a_vu.pdf, slide 9

Recommended blood pressure level 120 mm Hg for systolic over 80 mm Hg for diastolic.

Systolic blood pressure levels between 139-121 mm Hg and diastolic levels between 89-

81 mm Hg is considered pre-hypertension

Systolic blood pressure levels greater than 139 mm Hg and diastolic levels greater than 89 mm Hg is considered hypertension

Student Names: Brett Alcorn, Matt Arnold, Dana Flood

Preliminary Investigation

Preformed blood pressure tests on fellow students to get a better understanding of how blood pressure measurements are taken manually.

Then we analyzed pre-recorded sound files in the computer program Matlab to practice analyzing signals.

Generated a graph of the pressure signal and a graph of the stethoscope signal over the duration of the test.

Demodulated the signals by running them through a Matlab program and generated two new graphs.

Analysis of graphs gave us a better feeling on how to analyze signals and determine blood pressure measurements from those signals

Sensor Selection & Analog Development

Developed a circuit using a breadboard which conditioned the signal for processing.

Prior to processing and analyzing a signal the signal must first be conditioned in order for the DSP chip to be able to process it.

Signals received by the finger pulse sensor are small so they must first be amplified

Signals are also received in analog format where as the DSP chip processes digital signals.

As well as being amplified the circuit also converts the signal to digital so it can be processed.

Digital Processor Selection & Development

After building the circuit to process the signals we began processing pre-recorded signals using the program CCStudio.

Pressure signal

Finger pulse signal

Time (seconds)

We then began trials with the finger pulse sensor, attempting to obtain our own signals.

Upon obtaining a good signal se recorded the signal and processed it using the program

CCStudio in the same manner as the pre-recorded signals.

Pressure signal

Finger pulse signal

Time (seconds)

After processing our finger pulse signals we then plotted the pressure signal and finger pulse signals in order to get a better understanding of when to record systolic and diastolic pressures.

After perfecting our signal we ran a final analysis of our signals using a C program provided for us and we obtained our blood pressure measurements.

Conclusions & Further Development

We were able to successfully obtain automatic blood pressure measurements using the finger pulse sensor and the DSP chip.

Our final systolic blood pressure level was measured as 105 mm Hg and our final diastolic level was measured as 75 mm Hg.

We found the finger pulse sensor to be difficult to use and inaccurate. In many cases we were required to perform multiple tests in order to receive fairly accurate results.

The finger pulse sensor was very sensitive so it tended to pick up outside noise which interfered with our signal causing inaccuracies in our results.

The DSP chip was able to process the signals without a problems.

If we were to further develop an automatic blood pressure device using a finger pulse sensor and a DSP chip we would need to reduce the size of the circuit and DSP chip by removing all excess pieces and compacting everything onto one board.

By reducing everything to one board we can cheaply mass produce the board

The final step would be to embed all the components into one self-contained system for sale to consumers.

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