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Do kinematic gait parameters help to discriminate between fallers and non-fallers with Parkinson’s disease?
- Source :
- Clinical Neurophysiology. 132:536-541
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Objective Although a number of clinical factors have been linked to falls in Parkinson’s disease (PD), the diagnostic value of gait parameters remains subject to debate. The objective of this retrospective study was to determine to what extent the combination of gait parameters with clinical characteristics can distinguish between fallers and non-fallers. Methods Using a video motion system, we recorded gait in 174 patients with PD. The patients’ clinical characteristics (including motor status, cognitive status, disease duration, dopaminergic treatment and any history of falls or freezing of gait) were noted. The considered kinematic gait parameters included indices of gait bradykinesia and hypokinesia, asymmetry, variability, and foot clearance. After a parameters selection using an ANCOVA analysis, support vector machine algorithm was used to build classification models for distinguishing between fallers and non-fallers. Two models were built, the first included clinical data only while the second incorporated the selected gait parameters. Results The “clinical-only” model had an accuracy of 94% for distinguishing between fallers and non-fallers. The model incorporating additional gait parameters including stride time and foot clearance performed even better, with an accuracy of up to 97%. Conclusion Although fallers differed significantly from non-fallers with regard to disease duration, motor impairment or dopaminergic treatment, the addition of gait parameters such as foot clearance or stride time to clinical variables increased the model’s discriminant power. Significance: This predictive model now needs to be validated in prospective cohorts.
- Subjects :
- Male
medicine.medical_specialty
Parkinson's disease
Video Recording
STRIDE
Poison control
Kinematics
Sensitivity and Specificity
050105 experimental psychology
03 medical and health sciences
0302 clinical medicine
Physical medicine and rehabilitation
Gait (human)
Hypokinesia
Physiology (medical)
medicine
Humans
0501 psychology and cognitive sciences
Aged
Analysis of covariance
business.industry
05 social sciences
Parkinson Disease
Retrospective cohort study
Middle Aged
medicine.disease
Sensory Systems
Biomechanical Phenomena
Neurology
Accidental Falls
Female
Neurology (clinical)
medicine.symptom
Gait Analysis
business
human activities
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 13882457
- Volume :
- 132
- Database :
- OpenAIRE
- Journal :
- Clinical Neurophysiology
- Accession number :
- edsair.doi.dedup.....49ff6d63ee30130847da5a8547135da4