An assessment of autistic and parkinsonian movement profiles to inform selective classification algorithms.

Abstract

Background: Movement differences in autism have attracted growing attention in recent years. Anecdotally, autistic movement has been likened to that of Parkinson's Disease (PD). Given that PD assessments are primarily movement-based, it is important to ensure that autistic individuals are not scoring highly on PD diagnostic criteria due to autism-related movement differences. Quantifying overlap in movement profiles and identifying distinguishing features is essential, particularly given increased PD diagnosis rates in the autistic population.

Methods: We conducted the first direct comparison study of autistic and parkinsonian movement. Autistic individuals (N = 31), individuals with PD (N = 32) and control participants (N = 31) completed a Shapes Tracing Task and a Reaction Time Task. Kinematic features were compared between groups and classification algorithms were run to distinguish between groups.

Results: Groups were distinguishable based on kinematic features. The autistic group differed from both PD and control groups in speed modulation and sub-movements, and from the PD group in reaction time. Classification algorithms for clinical (autism and PD) versus non-clinical groups, and for autism versus PD, were most accurate when combining kinematic and questionnaire data. There were no kinematic similarities between autism and PD that were also distinct from controls.

Conclusions: Whilst kinematic features did not appear similar between autism and PD, they were informative for group classification. This proof-of-concept study highlights that movement-based metrics may aid in identifying whether someone belongs to a clinical group, and which one - suggesting potential for refining diagnostic approaches for both autism and PD.