BACKGROUND
Gait impairments including shuffling gait and hesitation are common in people with Parkinson’s disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD.
OBJECTIVE
This study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS).
METHODS
A total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated.
RESULTS
The results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (<i>F</i><sub>1,48</sub>=69.75, <i>P</i><.001, partial eta-square=0.59), initial step angle (<i>F</i><sub>1,48</sub>=15.56, <i>P</i><.001, partial eta-square=0.25), and last step angle (<i>F</i><sub>1,48</sub>=61.99, <i>P</i><.001, partial eta-square=0.56). Within the PD cohort, both the ALCT and DBS induced greater mean step angles (ACLT: <i>F</i><sub>1,38</sub>=5.77, <i>P</i>=.02, partial eta-square=0.13; DBS: <i>F</i><sub>1,52</sub>=8.53, <i>P</i>=.005, partial eta-square=0.14) and last step angles (ACLT: <i>F</i><sub>1,38</sub>=10, <i>P</i>=.003, partial eta-square=0.21; DBS: <i>F</i><sub>1,52</sub>=4.96, <i>P</i>=.003, partial eta-square=0.09), but no significant changes were observed in step time and number after the treatments. Additionally, these step angles were correlated with the Unified Parkinson's Disease Rating Scale, Part III score: mean step angle (single task: <i>r</i>=–0.60, <i>P</i><.001; dual task: <i>r</i>=–0.52, <i>P</i><.001), initial step angle (single task: <i>r</i>=–0.35, <i>P</i>=.006; dual task: <i>r</i>=–0.35, <i>P</i>=.01), and last step angle (single task: <i>r</i>=–0.43, <i>P</i>=.001; dual task: <i>r</i>=–0.41, <i>P</i>=.002).
CONCLUSIONS
This pilot study demonstrated that the gait angular characteristics, as quantified by the step angles, were sensitive to the disease severity of PD and, more importantly, can capture the effects of treatments on the gait, while the traditional metrics cannot. This indicates that these metrics may serve as novel markers to help the assessment of gait in those with PD as well as the rehabilitation of this vulnerable cohort.
An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease
