Next Article in Journal
Entropy Measures for Data Analysis: Theory, Algorithms and Applications
Next Article in Special Issue
Online Signature Analysis for Characterizing Early Stage Alzheimer’s Disease: A Feasibility Study
Previous Article in Journal
European Option Based on Least-Squares Method under Non-Extensive Statistical Mechanics
Previous Article in Special Issue
Heart Rate Dynamics in Patients with Obstructive Sleep Apnea: Heart Rate Variability and Entropy
Open AccessArticle

Multiscale Approximate Entropy for Gait Analysis in Patients with Neurodegenerative Diseases

by An-Bang Liu 1 and Che-Wei Lin 2,*
1
Department of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien 97002, Taiwan
2
Department of Biomedical Engineering and Medical Device Innovation Center, National Cheng Kung University, Tainan 70101, Taiwan
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(10), 934; https://doi.org/10.3390/e21100934
Received: 26 June 2019 / Revised: 16 September 2019 / Accepted: 18 September 2019 / Published: 25 September 2019
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. View Full-Text
Keywords: nonlinear analysis; multiscale approximate entropy; gait signals; neurodegenerative diseases nonlinear analysis; multiscale approximate entropy; gait signals; neurodegenerative diseases
Show Figures

Figure 1

MDPI and ACS Style

Liu, A.-B.; Lin, C.-W. Multiscale Approximate Entropy for Gait Analysis in Patients with Neurodegenerative Diseases. Entropy 2019, 21, 934.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop