open access

https://hdl.handle.net/2115/44037

Quantifying the regularity of time-series data : Application of approximate entropy to human movement analysis

日本語

posture

1998

日本バイオメカニクス学会

バイオメカニクス研究

2(2)

82-91

Approximate Entropy (Ap entropy) was developed as a method to quantify regularity of time-series data. The aim of this study was to examine problems in the application of Ap entropy to human movement data and to distinguish movement patterns by quantifying the regularity of experimental human movement data. The following results were obtained: 1) For a relatively periodic time-series function with a small number of periods，difference in both the number of data points and number of periods affected the Ap entropy value. Thus，for the application of Ap entropy，the number of data points and the number of periods should be made the same. 2) Under the experimental conditions of this study，the change in the Ap entropy value was in accordance with subjective judgment of movement patterns. This indicates that Ap entropy is an effective parameter for quantitatively distinguishing movement patterns in data that differ in time-series regularity.

学術雑誌論文

Version of Record

1343-1706