Multiscale approximate entropy for gait analysis in patients with neurodegenerative diseases

An Bang Liu, Che Wei Lin

研究成果: Article

摘要

Neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS), Parkinson's diseases (PD), and Huntington's disease (HD) are not rare neurological diseases. They affect different neurological systems and present various characteristic gait abnormalities. We retrieved gait signals of the right and left feet from a public domain on the Physionet. There were 13 patients with ALS, 15 patients with PD, 20 patients with HD and 16 healthy controls (HC).We used multiscale approximate entropy (MAE) to analyze ground reaction force on both feet. Our study shows that MAE increases with scales in all tested subjects. The group HD has the highest MAE and group ALS has the lowest MAE.We can differentiate ALS from HC by MAE, while scale factors > 10 in the left foot. There are few significant differences of MAE between the HC and HD.We found a good correlation of MAE between both feet in group ALS. In conclusion, our results indicate that MAE analysis of gait signals can be used for diagnosis and long-term assessment for ALS and probably HD. Similarity of MAE between both feet can also be a diagnostic marker for ALS.

原文English
文章編號934
期刊Entropy
21
發行號10
DOIs
出版狀態Published - 2019 十月 1

    指紋

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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