Time-frequency analysis of heart rate variability using short-time fourier analysis.
This study was done to introduce new parameters derived by time frequency analysis of heart rate variability data. Four simulation experiments were carried out to compare the short-time Fourier transform (STFT) analysis method to the traditional overall spectral analysis method. Sinusoidal signals were generated with identical total power in the high-frequency band, but varying time-frequency and time-amplitude information. The STFT method was also applied to heart rate variability data from the stages of normal human sleep. Data analysis included computation of the power in the high-frequency band by overall spectral analysis. The instability coefficients (ICs) of the frequency and power in the high-frequency band were derived by STFT analysis. The ICs derived by the STFT method were able to describe time-frequency and time-amplitude variations in sinusoidal signals which contained identical total power in a specified frequency range. The ICs of the frequency and power were able to differentiate variations in vagal activity between the stages of human sleep and waking. The ICs represent new parameters derived by the STFT method, and allow the detection and quantification of short-lasting time-frequency and time-amplitude variations that remain obscured by overall spectral analysis.
Elsenbruch
S
S
Thomas N Lynn Institute for Healthcare Research, Oklahoma City, Oklahoma 73112, USA. sigrid@earthling.net
Wang
Z
Z
Orr
W C
WC
Chen
J D
JD
D000328:Adult; D003198:Computer Simulation; D005260:Female; D005583:Fourier Analysis; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012894:Sleep Stages / Q000502:physiology; D013564:Sympathetic Nervous System / Q000502:physiology; D014630:Vagus Nerve / Q000502:physiology