SPARC: a new approach to quantifying gait smoothness in patients with Parkinson's disease

Background: Impairments in biomechanics and neural control can disrupt the timing and muscle pattern activation necessary for smooth gait. Gait is one of the most affected motor characteristics in Parkinson's disease (PD), but its smoothness has not been well-studied. This work applies the recently proposed spectral arc length measure (SPARC) to study, for the first time, gait in patients with PD. We hypothesized that the gait of patients with PD would be less smooth than that of healthy controls, as reflected in the SPARC measures. Methods: The gait of 101 PD patients and 39 healthy controls was assessed using an inertial sensor. Smoothness of gait was estimated with SPARC (respectively from acceleration and angular velocity signals, SPARC-Acc and SPARC-Gyro) and harmonic ratios. Correlations between SPARC, traditional gait measures and the motor part of the Unified Parkinson's Disease Rating Scale (UPDRS) were evaluated. Measurements and analysis were conducted with and without anti-PD medication. Results: SPARC measures were lower (less smooth) in PD than in controls (SPARC-Acc: PD: -6.11 +/- 0.74; CO: -5.17 +/- 0.79; p < 0.001). When comparing PD to controls, SPARC-Acc differed more than other measures of gait (i.e., largest effect size, which was > 1). SPARC measures were correlated with UPDRS motor score (r = -0.65), while they were independent of other measures of gait smoothness. PD gait in the on state was smoother than in the off state (p < 0.001). Conclusions: SPARC calculated from trunk acceleration and angular velocity signals provide valid measures of walking smoothness in PD. SPARC is sensitive to Parkinson's disease and PD medications and can be used of as another, complementary measure of the motor control of walking in PD.