Development and validation of an automated Trunk Impairment Scale 2.0 scoring system using rule-based classification.

IF 1.5 4区 医学 Q3 ENGINEERING, BIOMEDICAL Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine Pub Date : 2025-02-01 Epub Date: 2025-02-17 DOI:10.1177/09544119251317614
Tay Jia Yi, Zaidi Mohd Ripin, Mohamad Ikhwan Zaini Ridzwan, Muhammad Fauzinizam Razali, Yeo Ying Heng, Nur Akasyah Binti Jaafar, Alexander Tan Wai Teng, Hazwani Binti Ahmad Yusof, Muhammad Hafiz Hanafi
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Abstract

The Trunk Impairment Scale Version 2.0 (TIS 2.0) measures the motor impairment of the trunk after a stroke through the evaluation of dynamic sitting balance and co-ordination of trunk movement. Evaluations by physiotherapists depend on their ability in detecting minor changes in motion and observing limb movements and these can be time consuming and reduce their availability for rehabilitation work. An automated scoring system for TIS 2.0 was proposed to provide a more reproducible and standardized alternative to manual physiotherapist assessments. In the development phase, motion data from lay actors simulating stroke condition were collected using video motion capture system OpenCap. This data was utilized to create metrics and establish cut-off values for a rule-based classification. The discriminant abilities of the metrics were evaluated using the area under the curve (AUC). In the testing phase, the performance of the developed system was assessed on 19 stroke survivors (Berg Balance Scale score of 20-55) using both automated system and manual scoring by nine physiotherapists. The discriminant abilities of the features used in the dynamic sitting balance subscale are considered excellent to outstanding (AUC ≥ 0.717), and coordination subscale ranged from poor to outstanding (AUC ≥ 0.667). The automated scores aligned with physiotherapists' scores, achieving an average percentage of agreement 71.1%. The total TIS 2.0 scores generated by the automated method showed moderate correlation with the sum of mode-determined task scores (R = 0.526, p < 0.05). These findings suggest that the proposed automated system demonstrates comparable validity to assessments by physiotherapists.

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使用基于规则的分类开发和验证自动中继损伤量表2.0评分系统。
躯干损伤量表2.0版(TIS 2.0)通过评估动态坐位平衡和躯干运动协调性来衡量中风后躯干的运动损伤。物理治疗师的评估取决于他们检测运动的微小变化和观察肢体运动的能力,这些可能会耗费时间并减少他们的康复工作的可用性。提出了TIS 2.0的自动评分系统,以提供一个更可重复和标准化的替代手动物理治疗师评估。在开发阶段,使用视频动作捕捉系统OpenCap收集外行人模拟中风状态的运动数据。这些数据被用来创建度量标准,并为基于规则的分类建立截止值。用曲线下面积(AUC)评价指标的判别能力。在测试阶段,由9名物理治疗师使用自动系统和手动评分对19名中风幸存者(Berg Balance Scale评分为20-55分)的性能进行了评估。动态坐姿平衡子量表的特征判别能力为优至优(AUC≥0.717),协调性子量表的特征判别能力为差至优(AUC≥0.667)。自动评分与物理治疗师的评分一致,平均一致性百分比为71.1%。自动化方法生成的TIS 2.0总分与模式决定任务得分之和呈中等相关性(R = 0.526, p
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来源期刊
CiteScore
3.60
自引率
5.60%
发文量
122
审稿时长
6 months
期刊介绍: The Journal of Engineering in Medicine is an interdisciplinary journal encompassing all aspects of engineering in medicine. The Journal is a vital tool for maintaining an understanding of the newest techniques and research in medical engineering.
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