Objective: The objective of this study was to determine the most relevant biomechanical factors contributing to the risk of falling in those with Parkinson’s Disease (PD) using the miniBEST and other balance tasks.

Background: PD is a neurodegenerative disorder which affects functional mobility. Clinical scales, such as the miniBEST are often employed to provide an assessment into the disease state of those with PD. However, these scales are only semi-quantitative in their scoring. This research aimed to record biomechanical data, in the form of joint kinematics across the body and pressure distribution across the soles of the feet, to provide a more objective measure of the specific motor functionality and balance deficits which exist during the miniBEST in those with PD.

Method: For this study, 6 subjects with PD and 6 age-matched healthy controls were recruited. The recording involved the use of a series of inertial measurement units mounted across the body and arrays of pressure sensors placed on the insoles of the shoes. Data was recorded during each of the motor tasks included in the miniBEST, across the categories ‘Anticipatory Postural Adjustments’, ‘Reactive Postural Control’, ‘Sensory Orientation’, ‘Dynamic Gait’ and other supplementary motor tasks, such as a retropulsion test, five-time STS and rapid turns test, which were included as part of the analysis.

Results: Independent t-tests were employed followed by corrections for multiple comparisons. The results of this analysis showed that those with PD exhibited the greatest deficits in the ‘Postural Adjustments’ category. From the joint kinematic data, the deficit in joint kinematics was most notable in the waist velocity in the z-axis variable. From the pressure distribution data, the deficit in pressure distribution was most notable in the centre of pressure path length variable. This demonstrates the specific biomechanical deficits which lead to an increased risk of falling in those with PD, as demonstrated with the miniBEST.

Conclusion: This research shows the viability of performing this quantitative analysis of movement-based clinical scaling tools for assessing PD. This can be applied in a clinical setting to provide greater insights into disease progression and help identify those at risk of falling earlier before more subjective deficits can be found using clinical scaling tools.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/quantitative-analysis-of-the-biomechanical-contributors-during-the-minibest-clinical-scale-for-assessing-risk-of-falling-in-parkinsons-disease/