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- Title
Classification of Ataxic Gait.
- Authors
Vyšata, Oldřich; Ťupa, Ondřej; Procházka, Aleš; Doležal, Rafael; Cejnar, Pavel; Bhorkar, Aprajita Milind; Dostál, Ondřej; Vališ, Martin
- 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.
- Subjects
MUSCULOSKELETAL system diseases; MOTION detectors; GAIT disorders; QUALITY of life; RANDOM forest algorithms; GAIT in humans; CHILDREN with cerebral palsy
- Publication
Sensors (14248220), 2021, Vol 21, Issue 16, p5576
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s21165576