通过手绘形状图像自动评估儿童精细运动的发展。

IF 2.3 4区 医学 Q2 PEDIATRICS
Nai-Hsuan Hwang, Sheng-Shan Chen, Tun-Wen Pai, Mary Hsin-Ju Ko, Ya-Lan Yu, Hui-Ju Chen
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引用次数: 0

摘要

背景:精细运动技能与儿童神经系统发育密切相关,是儿童发育状况的重要指标。然而,临床评估需要大量的人力和物力资源。本研究提出了一种评估儿童精细运动技能发展的自动化评估机制,为发展评估提供了一种精简和资源高效的方法。方法:采用设计的系统对82例36 ~ 72月龄儿童的精细运动技能进行评估。孩子们被要求复制系统设计的五种几何形状:圆形、十字形、正方形、三角形和菱形。该系统使用基于人工智能的模型自动评估几何形状中的23个不同特征。然后,一个量身定制的评分系统给出了一个反映孩子精细运动技能成熟程度的分数。结果:共收集了81张试验组儿童的重复图画,并采用本研究开发的评估机制进行了自动评估。结果表明,精细运动技能成熟度与实际年龄呈正相关。此外,分数确定了精细运动发育迟缓的儿童。验证数据集中5种不同几何形状的自动分类模型的宏观f1得分和准确率分别为0.9236和0.9268。这些评估结果可以有效地支持早期干预和治疗工作。结论:该系统对不同几何形状的结构化绘制任务对儿童精细运动成熟度的自动评估具有重要的实用价值。本研究开发的评分方法对儿童精细运动技能的不同发展阶段提供了清晰的区分。该系统为评估儿童精细运动发育提供了一个有效的在线工具,从而为医生在随后的临床评估中提供了必要的初步参考信息,并显著减轻了医疗保健专业人员的负担。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic assessment of fine motor development in children through hand-drawn shape images.

Background: Fine motor skills are closely related to neurological maturity among children and serve as critical indicators of developmental status. However, clinical assessments require significant human and material resources. This study proposes an automated evaluation mechanism designed to assess the development of children's fine motor skills, offering a streamlined and resource-efficient approach to developmental assessment.

Methods: The designed system evaluated the fine motor skills of 82 children aged 36-72 months. The children were asked to replicate five geometric shapes designed by the system: circles, crosses, squares, triangles, and rhombuses. The system automatically assessed 23 distinct features across the geometric shapes using an artificial intelligence-based model. A tailored scoring system then assigned a score that reflected the child's level of fine motor skill maturity.

Results: A total of 81 replicated drawings from the children in the test group were collected and automatically assessed using the assessment mechanism developed in this study. The results demonstrated a strong positive correlation between fine motor skill maturity and practical age. Additionally, the scores identified children with delayed fine motor development. The macro F1-score and accuracy of the automatic classification models for the five different geometric shapes in the validation dataset were 0.9236 and 0.9268, respectively. These evaluation outcomes can effectively support early intervention and treatment efforts.

Conclusion: The system's structured drawing tasks for varying geometric shapes have substantial practical value for the automatic assessment of children's fine motor maturity. The scoring method developed in this study provides a clear distinction between the different developmental stages of children's fine motor skills. This system offers an effective online tool for assessing fine motor development among children, thereby providing essential preliminary reference information for physicians in subsequent clinical evaluations and significantly reducing the burden on healthcare professionals.

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来源期刊
CiteScore
3.10
自引率
0.00%
发文量
170
审稿时长
48 days
期刊介绍: Pediatrics and Neonatology is the official peer-reviewed publication of the Taiwan Pediatric Association and The Society of Neonatology ROC, and is indexed in EMBASE and SCOPUS. Articles on clinical and laboratory research in pediatrics and related fields are eligible for consideration.
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