Spectral Analysis of Human Stabilograms - Horikawa, Hiroshi; Unno, Tokuji; Shirato, Masaru (Equilibrium Research, 1991)
Some problems in the spectral analysis of human stabilograms are discussed. Power spectra were computed by the following three methods ; fast Fourier transform (FFT) method, autoregressive (AR) models and maximum entropy method (MEM). Power spectra were obtained from original time series (original waves) or separately from the high-pass filtered component (cut-off frequency 0.15 Hz). A distribution of the power spectra did not reveal any dominant frequency in original waves. The spectra derived from the high-pass filtered component revealed peaks in the majority of cases. It was essential for analyzing the power spectra to cut the lower frequency band from the original waves. FFT spectra showed large variance and high oscillation. Therefore, it was difficult to detect the dominant frequency. AR and MEM spectra showed stable and smooth spectral curves. Furthermore, since the influence of past sways were taken into account in AR models and the MEM method, these two methods were superior for the detection of periodicity of body sways.