Principal component analysis for ataxic gait using a triaxial accelerometer.
Akira Matsushima, Kunihiro Yoshida, Hirokazu Genno and 1 others
PMID 28464831WHAT IT FOUND
A computer model of accelerometer data identified specific movement patterns in ataxic gait.
Patients walked slower with shorter steps and swayed more side-to-side than controls. These patterns correlated with disease severity, offering a way to measure gait changes more precisely than clinical scales.
Key findings
01Patients with ataxia showed significantly different gait parameters compared to controls, including lower velocity, shorter step length, and higher side-to-side sway.
02Principal component analysis revealed that a specific score (the second principal component score) differed significantly between patients and controls and correlated with disease duration and clinical gait severity.
03The analysis identified low gait velocity, short steps, poor regularity, and high side-to-side body sway as the main characteristics of ataxic gait.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
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What it does not show
The study excluded patients who could not walk unaided or had severe gait impairment, so the findings do not apply to those with advanced disease. The longitudinal analysis included very few patients, particularly those with multiple system atrophy, making it difficult to confirm how the scores change over time. The method is not yet validated for routine clinical use and requires further testing to determine its practical utility. Patients with comorbid conditions affecting motor function were excluded, which limits generalizability to complex clinical populations.
Declared interests
The authors declared no competing interests. The study was approved by the Ethics Committee of Shinshu University School of Medicine.
The easy way to misread this
Do not assume this score is ready for clinical use. It was derived from a controlled laboratory setting with patients who could walk unaided, and the small sample size in the follow-up analysis means its ability to track disease progression over time is not yet firmly established.