• An assessment of autistic and...

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

Title:
An assessment of autistic and parkinsonian movement profiles to inform selective classification algorithms.
Authors:
Hickman LJ; MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK. Lydia.Hickman@mrc-cbu.cam.ac.uk.; Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK. Lydia.Hickman@mrc-cbu.cam.ac.uk., Fraser DS; Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK., Galea JM; Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK., Happé F; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK., Cook JL; Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK.
Source:
Journal of neurodevelopmental disorders [J Neurodev Disord] 2026 Jan 10; Vol. 18 (1), pp. 8. Date of Electronic Publication: 2026 Jan 10.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 101483832 Publication Model: Electronic Cited Medium: Internet ISSN: 1866-1955 (Electronic) Linking ISSN: 18661947 NLM ISO Abbreviation: J Neurodev Disord Subsets: MEDLINE
Imprint Name(s):
Publication: <2012-> : London : BioMed Central
Original Publication: New York : Springer
MeSH Terms:
Parkinson Disease*/physiopathology , Parkinson Disease*/diagnosis , Autistic Disorder*/physiopathology , Autistic Disorder*/diagnosis , Parkinsonian Disorders*/physiopathology , Parkinsonian Disorders*/diagnosis , Autism Spectrum Disorder*/physiopathology , Algorithms*, Biomechanical Phenomena/physiology ; Movement/physiology ; Reaction Time/physiology ; Humans ; Male ; Female ; Adult ; Middle Aged ; Young Adult ; Classification Algorithms
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Grant Information:
United Kingdom WT_ Wellcome Trust; Wellcome Mental Health Award (226778/Z/22/Z) United Kingdom WT_ Wellcome Trust; ERC-2017-StG Grant Agreement No. 757583 (Brain2Bee; Jennifer Cook PI) Horizon 2020; BB/M01116X/1 United Kingdom BB_ Biotechnology and Biological Sciences Research Council
Contributed Indexing:
Keywords: Autism; Classification; Movement; Parkinson’s disease
Entry Date(s):
Date Created: 20260110 Date Completed: 20260207 Latest Revision: 20260210
Update Code:
20260210
PubMed Central ID:
PMC12882580
DOI:
10.1186/s11689-025-09668-8
PMID:
41514394
Database:
MEDLINE

Weitere Informationen

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.
(© 2026. The Author(s).)

Declarations. Ethics approval and consent to participate: All participants gave fully informed consent in accordance with the Declaration of Helsinki. The experimental procedure was approved by the local Research Ethics Committee (ERN_18-1800B and ERN_16-0281AP5). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.