1. Classification of Ataxic Gait.
- Author
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Vyšata, Oldřich, Ťupa, Ondřej, Procházka, Aleš, Doležal, Rafael, Cejnar, Pavel, Bhorkar, Aprajita Milind, Dostál, Ondřej, and Vališ, Martin
- Subjects
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MUSCULOSKELETAL system diseases , *MOTION detectors , *GAIT disorders , *QUALITY of life , *RANDOM forest algorithms , *GAIT in humans , *CHILDREN with cerebral palsy - 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]
- Published
- 2021
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