Quantifying movement variability with fractals: From fall prediction to pharmaceutical evaluations and automated social distancing
James L. Fozard PhD*, William D. Kearns PhD
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AbstractBackground: Movement speed is by definition the distance between two points divided by the time spent traversing it. Movement path tortuosity (Fractal D) describes the actual path traversed; it increases as more random turns are added. Although time is not used in its calculation because it is a spatial measure, the quantification of path tortuosity has yielded a novel means to describe path characteristics that correlate with temporal measures.
Objective: After summarizing the initial published application of Fractal D to human movement paths, its applications to numerous areas are reviewed.
Method: Fractal D quantifies the degree a path deviates from a straight line, yielding an index that ranges from 1.0 (perfect straightness) to 2.0 (chaotic). Fractal D has been successfully used when subjects’ real time location systems data are the source.
Results: Research is summarized relating elevated path tortuosity to cognitive deficits in young and elderly adults, the prediction of future falls, movement paths during searches of virtual spaces, evaluation of drug effects, and automatic monitoring of multiple persons moving in common spaces and social distancing.
Conclusion: After its application from describing free movements of wild animals, the adaptation of Fractal D to human movement path variability has spread to several areas of study.Keywords: Fractal D, movement path tortuosity, cognitive decline, fall prediction, brain disease, aging
James L. Fozard PhD*, William D. Kearns PhD (2021). Quantifying movement variability with fractals: From fall prediction to pharmaceutical evaluations and automated social distancing. Gerontechnology, 20(2), 1-8
https://doi.org/10.4017/gt.2021.20.2.3.443.06