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Real-time ECG for objective stress level measurement
Linköping University, Department of Biomedical Engineering.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Today’s endeavor of performance and accomplishment might bring more efficiency in many ways, but it has a price. Stress related diseases have increased in numbers the last decades and the field of stress is an exceptionally live issue. Linkura is a company which partly works towards identifying and decreasing stress. To be able to monitor and detect stress in people’s daily life, an ECG-device is used.

This thesis is divided into two parts. The first part consisted of analyzing and comparing four different ECG based stress measures. These stress measures were RMSSD, Heart Rate, high frequency (HF) band and ratio between low and high frequency bands (LF/HF), last two based in frequency domain. These were taken from healthy test subjects for periods of relaxation where the stress level presumably would decrease. What could be seen for all measures was that they all showed a statistical significant decrease in stress level (p<0.05) during the relaxation period. LF/HF ratio was the one performing best and showed clearest decrease in stress.

Biofeedback is a growing treatment, or rather, health monitoring, which purpose is to gain awareness of physiological functions to manipulate them at will. The second part of the thesis compared two ECG-related respiratory components, to find out which one would be most suited for biofeedback purpose to lower stress in the form of breathing exercises. The two respiratory components investigated were beat to beat heart rate and R-peak amplitude. For this part, a real-time application in the form of a mobile application was created and connected to the ECG-device. This enabled real-time measurement, which was crucial for the second part. Different time and frequency based algorithms were made to compare the two respiratory components. What could be seen was that the beat to beat heart rate signal was the respiratory component following breathing pattern the most.

Place, publisher, year, edition, pages
2017. , p. 63
National Category
Medical Equipment Engineering
Identifiers
URN: urn:nbn:se:liu:diva-139217ISRN: LIU-IMT-TFK-A--17/546--SEOAI: oai:DiVA.org:liu-139217DiVA, id: diva2:1119950
Subject / course
Medical Technology
Available from: 2017-08-22 Created: 2017-07-05 Last updated: 2019-12-02Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
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More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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