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Identifying Multifractality Structure on Postural Sway

Newman ML Lau, Clifford ST Choy and Daniel HK Chow

From previous biomechanical researches, postural sway has been generally evaluated by descriptive statistics for the purpose of scientific and clinical purposes in analysing the variety of external perturbations and the corresponding responses by the human body. Although these approaches on analysing the responses enable the examinations on the characteristics and relationships between the input and output of different feedback systems, the stabilizing mechanism or the steady-state behaviour from the possible control schemes of the human body is not explicitly considered. In this research study, the multifractality structure on postural sway is identified by the numerical method on multifractal detrended fluctuation analysis. An experimental set of 11 healthy subjects were investigated by optical motion capture system from the retroreflective optical marker data attached on skin surface along the spinal curvature. It is observed that random walk characteristics, hence, correlations between present and history of data, are present in the time series. Multifractal detrended fluctuation analysis is further applied to get into the details about the correlation of data along the time series. The study reveals the degree of multifractality extracted from the data, and compares to shuffled data to ascertain the multifractality in spinal curvature movement is predominantly due to long-range correlations instead of probability distributions. The application of this computational technique attempts to describe the multiple strategies utilized by the motor control in response to static, yet swaying, human body posture.