用于评估银屑病关节炎患者精细运动技能的新型数字生物标记物:DaktylAct 基于触摸的严肃游戏方法

IF 6.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Eleni Vasileiou, Sofia B Dias, Stelios Hadjidimitriou, Vasilis Charisis, Nikolaos Karagkiozidis, Stavros Malakoudis, Patty de Groot, Stelios Andreadis, Vassilis Tsekouras, Georgios Apostolidis, Anastasia Matonaki, Thanos G Stavropoulos, Leontios J Hadjileontiadis
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引用次数: 0

摘要

银屑病关节炎(PsA)是一种影响关节的慢性炎症性疾病,严重影响患者的生活质量,欧洲银屑病管理指南强调了评估手部功能的重要性。在这里,我们介绍了一套新型数字生物标记物(dBMs),这些标记物来自于基于触摸屏的严肃游戏 DaktylAct,该游戏旨在对 PsA 引起的手部损伤(重点是精细运动技能)进行代理、游戏化和客观的评估。该游戏的设计实现了这一目标,即用户通过两指捏进/捏出和手腕旋转手势来控制大炮瞄准并击中目标。在游戏过程中产生的游戏指标(击中的目标和得分)和游戏动作的统计特征(平均值、标准偏差)(手势持续时间、施加的压力和手腕旋转角度)可作为信息的 dBM。DaktylAct 测试对象包括 16 名临床确诊的 PsA 患者和 9 名健康对照组(HC)。相关性分析表明,平均掐入持续时间与疾病活动度(DA)呈正相关,手腕旋转时施加压力的标准偏差与关节炎症呈负相关。逻辑回归模型的分类性能分别达到了 83% 和 91%,可将 HC 与低 DA(LDA)PsA 患者以及有关节炎症和无关节炎症的 PsA 患者区分开来。本文介绍的结果很有希望,是一个概念验证,为在更大的群体中进一步验证铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Digital Biomarkers for Fine Motor Skills Assessment in Psoriatic Arthritis: The DaktylAct Touch-based Serious Game Approach.

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.

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来源期刊
IEEE Journal of Biomedical and Health Informatics
IEEE Journal of Biomedical and Health Informatics COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
13.60
自引率
6.50%
发文量
1151
期刊介绍: IEEE Journal of Biomedical and Health Informatics publishes original papers presenting recent advances where information and communication technologies intersect with health, healthcare, life sciences, and biomedicine. Topics include acquisition, transmission, storage, retrieval, management, and analysis of biomedical and health information. The journal covers applications of information technologies in healthcare, patient monitoring, preventive care, early disease diagnosis, therapy discovery, and personalized treatment protocols. It explores electronic medical and health records, clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body area/sensor networks, and more. Integration-related topics like interoperability, evidence-based medicine, and secure patient data are also addressed.
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