Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease.
Parkinson’s disease
cerebellar ataxia
complexity index
gait complexity
gait pattern
gait variability
movement disorders
multiscale sample entropy
refine composite multiscale entropy
trunk acceleration time series
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
22 May 2023
22 May 2023
Historique:
received:
16
03
2023
revised:
14
04
2023
accepted:
16
05
2023
medline:
12
7
2023
pubmed:
11
7
2023
entrez:
11
7
2023
Statut:
epublish
Résumé
The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (
Identifiants
pubmed: 37430896
pii: s23104983
doi: 10.3390/s23104983
pmc: PMC10221101
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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