Transcript SIGNAL PROCESSING TECHNIQUES USED FOR THE ANALYSIS OF ACOUSTIC SIGNALS FROM HEART AND LUNGS TO DETECT PULMONARY EDEMA Pratibha Sharma Electrical, Computer and Energy Engineering.

SIGNAL PROCESSING TECHNIQUES
USED FOR THE ANALYSIS OF ACOUSTIC
SIGNALS FROM HEART AND LUNGS TO
DETECT PULMONARY EDEMA
Pratibha Sharma
Electrical, Computer and Energy Engineering Department,
University of Colorado-Boulder
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INTRODUCTION
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WHAT IS CONGESTIVE HEART
FAILURE?
Heart pumps out blood at
slower rate than normal heart.
Pumping power/capacity is
weaker than normal.
Cannot pump out enough
oxygen and nutrients to meet
the body’s needs.
Source: www.hearthealthyonline.com/
NEED FOR THE RESEARCH
 Congestive heart failure is a one of the leading
causes of death with nearly 250,000 deaths
every year worldwide.
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OBJECTIVE OF MY RESEARCH
To help the physician monitor changes in
the patient’s condition from
decompensated to compensated or
compensated to decompensated .
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EXPERIMENTAL DESIGN
Capture acoustic
signals of heart and
lungs using digital
stethoscope and
measuring an ECG
using Alivecore
Heart monitoring
machine.
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EXPERIMENTAL SET UP
Audacity Software
DS32a Digital Stethoscope
Alivecore Heart monitor
EQUIPMENT SPECIFICATION
1. Signal to noise ratio at zero gain for bell and
diaphragm modes for ds32a stethoscope is in
the range of 12db to 18 db.
2. Signal to noise ratio other than zero gain for
different modes and locations for my
stethoscope are in the range of 26 db to 45
db.
3. Minimum signal what stethoscope can
measure is 50 mV, 20Hz-1000Hz(sensitivity).
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SIGNAL PROCESSING TECHNIQUES
USED FOR ANALYSIS OF ACOUSTIC
HEART AND LUNG SIGNALS
• Fast Fourier Transform FFT
• Short Time Fourier Transform STFT
• Wavelet Transform
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RESULTS FROM FOURIER TRANSFORM
HEALTHY PERSON
COMPENSATED CHF PERSON
DECOMPENSATED CHF PERSON
1st Row - Signal in time domain for 10 seconds duration
2nd Row – Power Spectra of time domain signal respective to its above figure
RESULTS FOR HEART SIGNALS AT LOCATION
E FROM FFT
HEALTHY GROUP
AVERAGE
COMPENSATED GROUP
DECOMPENSATED GROUP
STANDARD DEVIATION
X Axis- Frequency in Hz with 600Hz as maximum frequency
Y Axis – Normalized Single Sided Amplitude Spectrum
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RESULTS FOR HEART SIGNALS AT LOCATION E ON 0.021 *
NORMALIZED MAXIMUM POWER
Fourier results at 2% Maximum normalized power of heart signal for healthy,
compensated and decompensated group
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DISCUSSION OF FOURIER TRANSFORM
RESULTS
• The spectra is too wide so hard to conclude
anything.
• Large variability in person to person results
due to different factors like heart variability,
body structures, lung capacity etc.
• Signals are non stationary therefore FFT is
not a right tool to use.
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ALTERNATIVE SIGNAL PROCESSING
OPTIONS
• Time- Frequency Analysis is required.
– STFT
• Narrow window leads to good time resolution and
poor frequency resolution
• Wide window leads to good frequency resolution
and poor time resolution
– Wavelet (localized time and frequency
resolution)
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DIFFERENT PHONOCARDIOGRAMS
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WAVELET ANALYSIS
High pass filter(g[n])
Low pass filter(g[n])
Signal convolved with filters
Under sampling by 2
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WAVELET ANALYSIS
1st level Decomposition
2nd level Decomposition
3rd level Decomposition
X Axis- Time
Y Axis- Frequency
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WAVELET ANALYSIS
Y
DIAGONAL
DETAILS
VERTICAL
DETAILS
DIAGONAL
DETAILS
HORIZONTAL APPROXIMATE HORIZONTAL
DETAILS
DIA
DETAILS
DETAILS
DIAGONAL
DETAILS
VERTICAL
DETAILS
X
DIAGONAL
DETAILS
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RESULTS OF LUNG SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF LUNG SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF LUNG SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF LUNG SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF HEART SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF HEART SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF HEART SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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RESULTS OF HEART SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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COMPARATIVE RESULTS OF SHORT DURATION HEART
SIGNALS(FROM ONE S1 TO NEXT S1)
X Axis- 8 different individuals with two measurements each
Y Axis - Blue bar shows Decompensated condition and red bar shows compensated condition
Note:- 1 and 6 patients are exception, 5th patient is the one with both bars showing
compensated condition.
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CONCLUSIONS
• Wavelet analysis is better approach to analyze acoustic
signals of heart and lungs
( non stationary signals).
• Wavelet analysis gave the promising results by showing the
consistent difference in spectra within the same individual
• Wavelet decomposed coefficients narrowed in spectra for
same duration of signals in between compensated and
decompensated stage for the individual.
• Mean value of vertical coefficients taken for 1heart beat
that is from one s1 sound to next s1 gave consistent
differences in compensated and decompensated stages of
the same patient.
• Variability between patients is so large , our analysis to
date , does not give clear distinction between the patients.
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RESULTS OF LUNG SIGNALS AT LOCATION E
FROM WAVELET FOR SAME PATIENTS
1st Row - First Measurement on 8 different individuals
2nd Row - Second Measurement on the same individuals. This row corresponds to 1st row
respectively.
3rd Row - measurement on healthy people.
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