Principal component analysis for ataxic gait using a triaxial accelerometer

Abstract

Background: It is quite difficult to evaluate ataxic gait quantitatively in clinical practice. The aim of this study was to analyze the characteristics of ataxic gait using a triaxial accelerometer and to develop a novel biomarker of integrated gate parameters for ataxic gait.

Methods: Sixty-one patients with spinocerebellar ataxia (SCA) or multiple system atrophy with predominant cerebellar ataxia (MSA-C) and 57 healthy control subjects were enrolled. The subjects were instructed to walk 10 m for a total of 12 times on a flat floor at their usual walking speed with a triaxial accelerometer attached to their back. Gait velocity, cadence, step length, step regularity, step symmetry, and degree of body sway were evaluated. Principal component analysis (PCA) was used to analyze the multivariate gait parameters. The Scale for the Assessment and Rating of Ataxia (SARA) was evaluated on the same day of the 10-m walk trial.

Results: PCA divided the gait parameters into four principal components in the controls and into two principal components in the patients. The four principal components in the controls were similar to those found in earlier studies. The second principal component in the patients had relevant factor loading values for gait velocity, step length, regularity, and symmetry in addition to the degree of body sway in the medio-lateral direction. The second principal component score (PCS) in the patients was significantly correlated with disease duration and the SARA score of gait (ρ = -0.363, p = 0.004; ρ = -0.574, p < 0.001, respectively).

Conclusions: PCA revealed the main component of ataxic gait. The PCS of the main component was significantly different between the patients and controls, and it was well correlated with disease duration and the SARA score of gait in the patients. We propose that this score provides a novel method to assess the severity of ataxic gait quantitatively using a triaxial accelerometer.

Keywords: Ataxic gait; Cerebellar ataxia; Gait analysis; Principal component analysis; SARA; Triaxial accelerometer.

Fig. 1

The distribution of the first and second principal component scores (PCSs). a Scatter diagram of the first and second PCSs in the patients and controls. Both scores were significantly higher in the controls than in the patients. b The distribution of the second PCS among the controls and the groups divided according to the SARA score of gait. The bars show the 95% confidence intervals. The number of the subjects in each group was 57 in controls, 61 in patients (2 with the SARA score of gait 0, 7 with score 1, 16 with score 2, 28 with score 3, 1 with score 4, 3 with score 5, and 4 with score 6). As there was only 1 subject in the patients with the score 4, the confidence interval in that group is not shown. *p < 0.05

Fig. 2

The chronological change of the first and second principal component scores. a The change of the first principal component scores. b The change of the second principal component scores. The bars show the 95% confidence intervals. The number of subjects in each group was 18 in the controls, 2 in SCA6, 8 in SCA31, and 5 in MSA-C