IMF-based chaotic characterization of AP and ML visually-driven postural responses

Hanif Azhar; Guillaume Giraudet; Jocelyn Faubert

doi:10.1117/12.2003047

14 March 2013 IMF-based chaotic characterization of AP and ML visually-driven postural responses

Hanif Azhar, Guillaume Giraudet, Jocelyn Faubert

Proceedings Volume 8651, Human Vision and Electronic Imaging XVIII; 86511F (2013) https://doi.org/10.1117/12.2003047
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

The objective was to analyze visually driven postural responses and characterize any non-linear behaviour. We recorded physiological responses for two adults, 260 trials each. The subjects maintained quite stance while fixating for four seconds within an immersive room, EON Icube, where the reference to the visual stimuli, i.e., the virtual platform, randomly oscillated in Gaussian orientation 90° and 270° for antero-posterior (AP), and, 0° and 180° for medio-lateral (ML) at three different frequencies (0.125, 0.25, and 0.5 Hz). We accomplished stationary derivatives of posture time series by taking the intrinsic mode functions (IMFs). The phase space plot of IMF shows evidence of the existence of non-linear attractors in both ML and AP. Correlation integral slope with increasing embedding dimension is similar to random white noise for ML, and similar to non-linear chaotic series for AP. Next, recurrence plots indicate the existence of more non-linearity for AP than that for ML. The patterns of the dots after 200^th time stamp (near onset) appears to be aperodic in AP. At higher temporal windows, AP entropy tends more toward chaotic series, than that of ML. There are stronger non-linear components in AP than that in ML regardless of the speed conditions.

Citation Download Citation

Hanif Azhar, Guillaume Giraudet, and Jocelyn Faubert "IMF-based chaotic characterization of AP and ML visually-driven postural responses", Proc. SPIE 8651, Human Vision and Electronic Imaging XVIII, 86511F (14 March 2013); https://doi.org/10.1117/12.2003047

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KEYWORDS

Chaos

Visualization

Glasses

Visual analytics

Statistical analysis

Radon

Control systems

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