Multitaper analysis of HRV power and its stress-related correlation to respiration frequency
(2018) MASM01 20181Mathematical Statistics
- Abstract
- In this Master thesis, different multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power.
The methods are applied first on ARMA-process data, then on the integrated pulse frequency modulation (IPFM) data simulations, where the evaluation is performed by calculating the bias and standard deviation of the narrow-banded HRV power and its correlation with respiratory frequency. The results show that the Thomson multipaper and the peak-matched multitaper has each own pros and cons on different type of signals and that the Thomson multitapers are the best giving the... (More) - In this Master thesis, different multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power.
The methods are applied first on ARMA-process data, then on the integrated pulse frequency modulation (IPFM) data simulations, where the evaluation is performed by calculating the bias and standard deviation of the narrow-banded HRV power and its correlation with respiratory frequency. The results show that the Thomson multipaper and the peak-matched multitaper has each own pros and cons on different type of signals and that the Thomson multitapers are the best giving the strongest negative correlation. The second aim is to check whether the correlation deviates between subjects with different level of stress. A total num-
ber of 47 individuals, divided into 3 groups had their respirations and heart rates recorded. A clear difference is found indicating that the more stressed the stronger the correlation. (Less) - Popular Abstract
- As mental states and stress conditions are suggested to have diverse impacts on heart rate variability (HRV), it is of great interest to investigate how HRV reflects differently the modulation to the rhythm of heart by the control of the sympathetic and parasympathetic nervous systems under different stress states.
\indent Three multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power. The aim of this thesis is to first evaluate the performance of different multitaper methods on simulated data by calculating the bias and standard deviation of the band power... (More) - As mental states and stress conditions are suggested to have diverse impacts on heart rate variability (HRV), it is of great interest to investigate how HRV reflects differently the modulation to the rhythm of heart by the control of the sympathetic and parasympathetic nervous systems under different stress states.
\indent Three multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power. The aim of this thesis is to first evaluate the performance of different multitaper methods on simulated data by calculating the bias and standard deviation of the band power estimation, and by comparing the correlation between respiratory frequency and HRV power. Secondly, this thesis also aims to find whether the correlation deviates between subjects with different levels of stress as it has been found that stress has negative impact on HRV power.
\indent The result shows that on simulated data the peak-matched multitaper seems to be the best method for spectrum estimation giving the least deviation, and that the Thomson multitaper gives a slightly higher coherence (negative correlation). On real data, a stronger negative correlation is found in high stressed group than in low stressed group given the least HRV power in high stressed group.As mental states and stress conditions are suggested to have diverse impacts on heart rate variability (HRV), it is of great interest to investigate how HRV reflects differently the modulation to the rhythm of heart by the control of the sympathetic and parasympathetic nervous systems under different stress states.
\indent Three multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power. The aim of this thesis is to first evaluate the performance of different multitaper methods on simulated data by calculating the bias and standard deviation of the band power estimation, and by comparing the correlation between respiratory frequency and HRV power. Secondly, this thesis also aims to find whether the correlation deviates between subjects with different levels of stress as it has been found that stress has negative impact on HRV power.
\indent The result shows that on simulated data the peak-matched multitaper seems to be the best method for spectrum estimation giving the least deviation, and that the Thomson multitaper gives a slightly higher coherence (negative correlation). On real data, a stronger negative correlation is found in high stressed group than in low stressed group given the least HRV power in high stressed group. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8949861
- author
- He, Zite
- supervisor
- organization
- course
- MASM01 20181
- year
- 2018
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Multitaper (multiple windows), Heart rate variability (HRV), Spectrum anal- ysis, Integrated pulse frequency modulation (IPFM), High frequency band (HF), Thomson multitaper (TH MW), Peak-matched multitaper (PM MW), Correlation.
- language
- English
- id
- 8949861
- date added to LUP
- 2018-06-15 08:08:16
- date last changed
- 2018-06-15 08:18:22
@misc{8949861,
abstract = {{In this Master thesis, different multitaper methods are implemented to estimate the spectra of respiratory signals and HRV data, and further to estimate the correlation between the respiratory center frequency and the narrow-banded high frequency band of HRV power.
The methods are applied first on ARMA-process data, then on the integrated pulse frequency modulation (IPFM) data simulations, where the evaluation is performed by calculating the bias and standard deviation of the narrow-banded HRV power and its correlation with respiratory frequency. The results show that the Thomson multipaper and the peak-matched multitaper has each own pros and cons on different type of signals and that the Thomson multitapers are the best giving the strongest negative correlation. The second aim is to check whether the correlation deviates between subjects with different level of stress. A total num-
ber of 47 individuals, divided into 3 groups had their respirations and heart rates recorded. A clear difference is found indicating that the more stressed the stronger the correlation.}},
author = {{He, Zite}},
language = {{eng}},
note = {{Student Paper}},
title = {{Multitaper analysis of HRV power and its stress-related correlation to respiration frequency}},
year = {{2018}},
}