A Quantitative, Digital Method to Analyze Human Figure Drawings as a Tool to Assess Body Representations Distortions in Stroke Patients.

Détails

ID Serval
serval:BIB_55E38568FE68
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
A Quantitative, Digital Method to Analyze Human Figure Drawings as a Tool to Assess Body Representations Distortions in Stroke Patients.
Périodique
IEEE open journal of engineering in medicine and biology
Auteur⸱e⸱s
Martinelli I., Konik S., Guanziroli E., Tharayil J., Foglia C., Alemu M.M., Colombo M., Specchia A., Serino A., Molteni F., Bassolino M.
ISSN
2644-1276 (Electronic)
ISSN-L
2644-1276
Statut éditorial
Publié
Date de publication
2023
Peer-reviewed
Oui
Volume
4
Pages
278-283
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
Human figure drawings are widely used in clinical practice as a qualitative indication of Body Representations (BRs) alterations in stroke patients. The objective of this study is to present and validate the use of a new app called QDraw for the quantitative analysis of drawings and to investigate whether this analysis can reveal distortions of BRs in chronic stroke patients.
QDraw has proven to generate reliable data as compared to manual scoring and in terms of inter-rater reliability, as shown by the high correlation coefficients. Moreover, human figure drawings from chronic stroke patients demonstrated a distortion of upper limb perception, as shown by a significantly higher arm length asymmetry compared to legs, whereas no difference was found in healthy controls.
The present study supports the use of quantitative, digital methods (the QDraw app) to analyze human figure drawings as a tool to evaluate BRs distortions in stroke patients.
Mots-clé
Body representations, drawings, human figure, sensorimotor deficits, stroke
Pubmed
Web of science
Open Access
Oui
Création de la notice
12/01/2024 10:51
Dernière modification de la notice
27/01/2024 8:36
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