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Classification of Ataxic Gait.
- Source :
- Sensors (14248220); Aug2021, Vol. 21 Issue 16, p5576-5576, 1p
- Publication Year :
- 2021
-
Abstract
- Gait disorders accompany a number of neurological and musculoskeletal disorders that significantly reduce the quality of life. Motion sensors enable high-quality modelling of gait stereotypes. However, they produce large volumes of data, the evaluation of which is a challenge. In this publication, we compare different data reduction methods and classification of reduced data for use in clinical practice. The best accuracy achieved between a group of healthy individuals and patients with ataxic gait extracted from the records of 43 participants (23 ataxic, 20 healthy), forming 418 segments of straight gait pattern, is 98% by random forest classifier preprocessed by t-distributed stochastic neighbour embedding. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 21
- Issue :
- 16
- Database :
- Complementary Index
- Journal :
- Sensors (14248220)
- Publication Type :
- Academic Journal
- Accession number :
- 152146130
- Full Text :
- https://doi.org/10.3390/s21165576