发表机构
Télécom SudParis, Institut Polytechnique de Paris（巴黎理工大学电信南巴黎学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出并验证了一项开放、常模参照的测量工具，利用136个在线书写特征构建12域偏差画像，在257名儿童队列中区分书写障碍，并公开全部资源。
AI 中文摘要
在数字化写字板上捕获的在线书写可产生数百种运动学、时间、空间和动态特征。这些特征很少被组织成可解释、可复用的构念，而且尽管标准化测试对书写产品进行了常模化，但尚无公开可用的工具将儿童的书写过程相对于经核实的典型参考进行定位。我们引入并验证了一项开放的测量工具，用于从句子级在线书写中对发展性书写障碍儿童的书写过程偏差进行画像分析。该工具包括：(i) 一个仅基于文献的词汇表，在任何队列分析之前固定，将136个在线书写特征组织成12个书写过程域；(ii) 一个经年龄和性别调整的常模参考框架，仅基于经核实的典型儿童拟合，将这些特征转化为具有每个儿童自举不确定性的12轴偏差画像。我们在DiaGraMo队列（N=257名8-12岁捷克儿童；110名经核实的典型儿童，147名书写障碍儿童）上确立了其测量特性：词汇表在结构上具有连贯性，参考框架经过校准、简约且无泄漏。在同一队列中，12个域中有5个在BH q<.05（Cliff's δ +0.19至+0.51）下区分两组，涉及空间、时间和笔方向过程，且96.5%的参与者×域得分具有窄于一个z单位的自举置信区间。未训练任何分类器：该工具报告不确定性感知的偏差得分而非诊断标签，其离群率并非诊断率。词汇表、分析代码以及一个可对新参与者进行评分的开放参考实现均已公开发布，为书写和书写障碍研究人员提供了一个可复用、经过验证的工具，用于将个体儿童置于常模参考中进行定位。
英文摘要
Online handwriting captured on digitizing tablets yields hundreds of kinematic, temporal, spatial, and dynamic features. These features are rarely organized into interpretable, reusable constructs, and, although standardized tests norm the handwritten product, no openly available instrument places a child's handwriting process relative to a verified-typical reference. We introduce and validate an open measurement instrument for profiling handwriting-process deviations in children with developmental dysgraphia from sentence-level online handwriting. The instrument comprises (i)~a literature-only vocabulary, fixed before any cohort analysis, organizing 136 online-handwriting features into 12 handwriting-process domains, and (ii)~an age- and sex-adjusted normative reference framework, fit on verified-typical children only, that turns those features into a 12-axis deviation profile with per-child bootstrap uncertainty. We establish its measurement properties on the DiaGraMo cohort (N=257 Czech children aged 8--12; 110 verified-typical, 147 with dysgraphia): the vocabulary is structurally coherent, and the reference is calibrated, parsimonious, and leakage-free. On the same cohort, five of twelve domains separate the groups at BH~$q<.05$ (Cliff's~$δ$ +0.19 to +0.51), on spatial, temporal, and pen-orientation processes, and 96.5\% of participant~$\times$~domain scores have a bootstrap CI narrower than one z-unit. No classifier is trained: the instrument reports uncertainty-aware deviation scores rather than a diagnostic label, and its outlier rate is not a diagnostic rate. The vocabulary, the analysis code, and an open reference implementation that scores new participants are all openly released, giving handwriting and dysgraphia researchers a reusable, validated instrument for situating individual children against a normative reference.
