Beyond clinical scales: an observational study on instrumental gait analysis and biomechanical patterns in patients with Parkinson's disease

Abstract

Introduction: Parkinson's disease (PD), a common neurodegenerative disorder affecting motor functions, is associated with abnormal gait patterns characterized by altered kinematic, kinetic, and electrophysiological parameters. This observational study aims to instrumentally identify and quantify these gait dysfunctions in PD patients compared to normal values from healthy subjects.

Methods: Sixty-nine PD patients underwent clinical and instrumental evaluations to assess gait. Demographic and clinical data were collected before motor assessment. Clinical scales evaluated the level of impairment, gait, balance, risk of falls and ability to complete activities of daily living. Instrumental evaluations were conducted using optoelectronic, force plates and electromyographic (EMG) systems in a motion analysis laboratory. Statistical analysis involved a non-parametric test to compare pathological and normal data, clustering methods to identify groups based on clinical evaluations, and a combination of non-parametric analysis and linear models to assess dependencies on clinical scales.

Results: The results showed that PD patients had significant gait kinematic differences compared to normal values, with increased temporal and shortened spatial parameters. In addition, PD patients were grouped into four clusters based on clinical scales. While some gait features were influenced by clinical scales reflecting impairment, gait and balance, and independence, others were more affected by the perceived fear of falling (FoF).

Discussion: In conclusion, the study identified specific biomechanical gait dysfunctions in kinematic, kinetic, and electrophysiological parameters in PD patients, undetectable by standard clinical scales. Additionally, higher FoF was associated with dysfunctional biomechanical patterns, independent of impairment severity, gait and balance dysfunction, or overall independence.

Keywords: Parkinson’s disease; biomechanics of gait; fear of falling; gait analysis; neurorehabilitation; neurorehabilitation gait analysis; optoelectronic motion capture system.

FIGURE 1

BTS SMART-Clinic software. The figure shows the data processing procedure for one of the participants. A 3D human body model, reconstructed using the optoelectronic system, is displayed along with the detected events and the synchronized video recordings from the gait trial.

FIGURE 2

Kinematic gait parameters. The figure shows some of the temporal and spatial kinematic parameters, reported as mean ± standard deviation (A) Compares temporal parameters (gait stride, stance and swing duration) between participants with PD (red) and healthy subjects (grey) (B) Shows the same comparison for spatial parameters (stride length, step length and step width). Statistical difference significance, evaluated using Wilcoxon rank sum test, is reported as *** < 0.001, ** < 0.01 and * < 0.05.

FIGURE 3

Distribution of clinical scale scores across identified clusters. The figure shows clustering results based on clinical scales, with a colour gradient representing severity levels on each scale. The gradient ranges from less severe (green) to more severe (red). This allows for an accurate visualization of severity patterns specific to each cluster and clinical scale.

FIGURE 4

Motor clinical scales and instrumental biomechanical gait parameters. The left column shows instrumental parameters (C,E,G) with trends similar to BBS (A) while the right column includes those (D,F,H,I) following trends similar to FES-I (B). Dependency of instrumental parameters from both clinical scales (A,B) was statistically confirmed. Each panel shows the box plots for the four identified clusters (represented by different colors), with red crosses indicating outlier values.