Novel Digital Biomarkers for Fine Motor Skills Assessment in Psoriatic Arthritis: The DaktylAct Touch-based Serious Game Approach

• Published in: IEEE journal of biomedical and health informatics Vol. PP; pp. 1 - 14
• Main Authors: Vasileiou, Eleni, Dias, Sofia B., Hadjidimitriou, Stelios, Charisis, Vasilis, Karagkiozidis, Nikolaos, Malakoudis, Stavros, de Groot, Patty, Andreadis, Stelios, Tsekouras, Vassilis, Apostolidis, Georgios, Matonaki, Anastasia, Stavropoulos, Thanos G., Hadjileontiadis, Leontios J.
• Format: Journal Article
• Language: English
• Published: United States IEEE 29-10-2024
• Subjects: Accuracy; Arthritis; Bioinformatics; Biomarkers; DaktylAct; Digital biomarkers (dBMs); Diseases; Fine motor skills assessment; Motors; Pain; Psoriasis; Psoriatic arthritis (PsA); Serious Game; Smart phones; Wrist
• ISSN: 2168-2194; 2168-2208; 2168-2208
• DOI: 10.1109/JBHI.2024.3487785

Psoriatic Arthritis (PsA) is a chronic, inflammatory disease affecting joints, substantially impacting patients' quality of life, with European guidelines for managing PsA emphasizing the importance of assessing hand function. Here, we present a set of novel digital biomarkers (dBMs) derived from a touchscreen-based serious game approach, DaktylAct, intended as a proxy, gamified, objective assessment of hand impairment, with emphasis on fine motor skills, caused by PsA. This is achieved by its design, where the user controls a cannon to aim at and hit targets using two finger pinch-in/out and wrist rotation gestures. In-game metrics (targets hit and score) and statistical features (mean, standard deviation) of gameplay actions (duration of gestures, applied pressure, and wrist rotation angle) produced during gameplay serve as informative dBMs. DaktylAct was tested on a cohort comprising 16 clinically verified PsA patients and nine healthy controls (HC). Correlation analysis demonstrated a positive correlation between average pinch-in duration and disease activity (DA) and a negative correlation between standard deviation of applied pressure during wrist rotation and joint inflammation. Logistic regression models achieved 83% and 91% classification performance discriminating HC from PsA patients with low DA (LDA) and PsA patients with and without joint inflammation, respectively. Results presented here are promising and create a proof-of-concept, paving the way for further validation in larger cohorts.