Development of Smartphone Application for Pulmonary Function Testing - - PowerPoint PPT Presentation

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Development of Smartphone Application for Pulmonary Function Testing - - PowerPoint PPT Presentation

Development of Smartphone Application for Pulmonary Function Testing Dmitry Baganov, Alexander Borodin Petrozavodsk State University AMICT2015 conference May 1315, Petrozavodsk, Russia Dmitry Baganov CardiaCare AMICT2015 1 / 12


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SLIDE 1

Development of Smartphone Application for Pulmonary Function Testing

Dmitry Baganov, Alexander Borodin

Petrozavodsk State University

AMICT’2015 conference May 13–15, Petrozavodsk, Russia

Dmitry Baganov CardiaCare AMICT’2015 1 / 12

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SLIDE 2

Respiratory Diseases

Facts by WHO

  • Approx. 64 million people

suffered from COPD (and 235 million from asthma) worldwide in 2004

  • Approx. 5% of deaths every

year Not curable but treatment can slow the progress of the disease Risk factors Air pollution Occupational dusts and chemicals Tobacco use Unhealthy diet Physical inactivity

Dmitry Baganov CardiaCare AMICT’2015 2 / 12

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SLIDE 3

Algorithm of Abnormalities Detection

Algorithm 1 Diagnosing obstruction or restrictive/mixed abnormalities if FVC ≥ LLN then if FEV1 / FVC ≤ LLN & then diagnose normal case else diagnose obstruction end if if FEV1 / FVC ≥ 0.55 & FVC < 85% then diagnose restrictive or mixed abnormalities else diagnose obstruction end if end if

1

1from "Diagnostic Spirometry in Primary Care. Proposed standards for general

practice...-by M. L. Levy et. al.

Dmitry Baganov CardiaCare AMICT’2015 3 / 12

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SLIDE 4

General Algorithm Breath Analysis

Algorithm

Writing breathing in WAV format. Detection phase of inhalation / exhalation. Clean signal from the unnecessary information. The calculation of time and energy between inhalation and exhalation. Calculation of lung volume, etc on the basis of the data obtained. Processing of results.

Dmitry Baganov CardiaCare AMICT’2015 4 / 12

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SLIDE 5

Look at Signals

Рис.: Respiration signal obtained by the microphone

Dmitry Baganov CardiaCare AMICT’2015 5 / 12

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SLIDE 6

Look at Signals

Рис.: Respiration signal after separation of phases of inhalation and exhalation.

Dmitry Baganov CardiaCare AMICT’2015 6 / 12

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SLIDE 7

Lung Capacity

Forced volume capacity2 FVCm = 0.1524 × height − 0.0214 × age − 4.6500 FVCf = 0.1247 × height − 0.0216 × age − 3.5900 Forced expiratory volume after one second FEV1m = 0.1052 × height − 0.0244 × a − 2.1900 FEV1f = 0.0869 × height − 0.0255 × a − 1.5780

2from "Lung Capacity Estimation Through Acoustic Signal of Breath"

by Ahmad Abushakra and Miad Faezipour

Dmitry Baganov CardiaCare AMICT’2015 7 / 12

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SLIDE 8

Estimated Lung Capacity

Forced volume capacity assessment based on breath sound analysis3 FVCm = 15e 100(0.1524 × height − 0.0214 × age − 4.65) × t FVCf = 15e 100(0.1247 × height − 0.0216 × age − 3.5900) × t Here t is the average time duration of exhale and inhale and e is the signal energy. P.S These equations were derived using empirical data and estimation.

3from "Lung Capacity Estimation Through Acoustic Signal of Breath"

by Ahmad Abushakra and Miad Faezipour

Dmitry Baganov CardiaCare AMICT’2015 8 / 12

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SLIDE 9

Some Results

Рис.: My spirogram.

Dmitry Baganov CardiaCare AMICT’2015 9 / 12

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SLIDE 10

Some Results

Рис.: Type of spirograms.

Dmitry Baganov CardiaCare AMICT’2015 10 / 12

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SLIDE 11

Data Processing Methods

Calculating the results on the phone.

◮ You don’t need the Internet,

but need a powerful phone.

Calculating results in the cloud.

◮ Any phone, but need internet. Dmitry Baganov CardiaCare AMICT’2015 11 / 12

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SLIDE 12

Future Plans

Conduct experiments and to improve the results of the research. Modifying an application to work in the cloud. Modifying data analysis.

Dmitry Baganov CardiaCare AMICT’2015 12 / 12