In this paper, the results of different multiple window spectrum analysis methods are compared in the estimation of heart rate variability (HRV) power spectra, in the high frequency band (HF), around 0.25 Hz, related to respiratory sinus arrhythmia (RSA). The evaluation is performed by simulating different spectrum shapes and peak frequency locations and calculating the mean squared error of a frequency range close around the strongest spectral peak. The results show that it is preferable to use the Peak Matched Multiple Windows in most situations, but the Welch method and the Sinusoid Multiple Windows can be as reliable in certain aspects
Heart Rate Variability (HRV) is one of the reliable quantitative markers of the Automatic Nervous Sy...
This paper describes a method to adapt the spectral features extracted from heart rate variability (...
The work deals with the spectral analysis of heart rate variability (HRV), one of the methods assess...
In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, bet...
ECG monitoring of heart rate variability (HRV) in a noninvasive method for the evaluation of cardiov...
In the last decades, one of the main challenges in the study of heart rate variability (HRV) signals...
The tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerab...
In this paper a methodological approach for the analysis of nonstationary heart rate variability (HR...
Abstract — In this paper a methodological approach for the analysis of nonstationary heart rate vari...
In this Master thesis, different multitaper methods are implemented to estimate the spectra of respi...
We investigated how the parameters of the spectral analysis affect standard deviation and error of t...
Heart rate variability (HRV) analysis is increasingly used in anaesthesia and intensive care monitor...
Cardiovascular variability signals provide information about the functioning of the autonomous nervo...
In this paper, we present new insights on classical spectral measures for heart rate variability (HR...
A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the hear...
Heart Rate Variability (HRV) is one of the reliable quantitative markers of the Automatic Nervous Sy...
This paper describes a method to adapt the spectral features extracted from heart rate variability (...
The work deals with the spectral analysis of heart rate variability (HRV), one of the methods assess...
In this paper, we evaluate the correlation estimate, based on multiple window spectrum analysis, bet...
ECG monitoring of heart rate variability (HRV) in a noninvasive method for the evaluation of cardiov...
In the last decades, one of the main challenges in the study of heart rate variability (HRV) signals...
The tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerab...
In this paper a methodological approach for the analysis of nonstationary heart rate variability (HR...
Abstract — In this paper a methodological approach for the analysis of nonstationary heart rate vari...
In this Master thesis, different multitaper methods are implemented to estimate the spectra of respi...
We investigated how the parameters of the spectral analysis affect standard deviation and error of t...
Heart rate variability (HRV) analysis is increasingly used in anaesthesia and intensive care monitor...
Cardiovascular variability signals provide information about the functioning of the autonomous nervo...
In this paper, we present new insights on classical spectral measures for heart rate variability (HR...
A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the hear...
Heart Rate Variability (HRV) is one of the reliable quantitative markers of the Automatic Nervous Sy...
This paper describes a method to adapt the spectral features extracted from heart rate variability (...
The work deals with the spectral analysis of heart rate variability (HRV), one of the methods assess...