Linear and nonlinear analysis of human postural sway

Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Mühendislik Bilimleri Bölümü, Türkiye

Tezin Onay Tarihi: 2008




Human upright posture exhibits an everlasting oscillatory behavior of complex nature, called as human postural sway. Variations in the position of the Center-of-Pressure (CoP) were used to describe the human postural sway. In this study; CoP data, which has experimentally been collected from 28 different subjects (14 males and 14 females with their ages ranging from 6 to 84), who were divided into 4 groups according to their ages has been analyzed. The data collection from each of the subjects was performed in 5 successive trials, each of which has lasted for 180-seconds long. Linear analysis methods such as the variance/standard deviation, Fast Fouriér Transformation, and Power Spectral Density estimates were applied to the detrended CoP signal of human postural sway. Also the Run test and Ensemble averages methods were used to search for stationarity and ergodicity of the CoP signal respectively. Furthermore, in order to reveal the nonlinear characteristics of the human postural sway, its dynamics were reconstructed in m-dimensional state space from the CoPx signals. Then, the correlation dimension (D2) estimates from the embedded dynamics were calculated. Additionally, the statistical and dynamical measures computed were checked against any significant changes, which may occur during aging. The results of the study suggested that human postural sway is a stationary process when 180-second long biped quiet stance data is considered. In addition, it exhibits variable dynamical structure complex in nature (112 deterministic chaos versus 28 stochastic time series of human postural sway) for five successive trials of 28 different subjects. Moreover, we found that groups were significantly different in the correlation dimension (D2) measure (p≤0.0003). Finally, the behavior of the experimental CoPx signals was checked against two types of linear processes by using surrogate data method. The shuffled CoPx signals (Surrogate I) suggested that temporal order of CoPx is important; however, phase-randomization (Surrogate II) did not change the behavioral characteristics of the CoPx signal.