基于知识图谱的卒中后步态评估系统:初步研究

IF 2.3 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Yiran Jiao , Zengkun Liu , Stacey Reading , Marie-Claire Smith , Jianhua Lin , Yanxin Zhang
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引用次数: 0

摘要

仪器步态分析(IGA)已广泛应用于研究,但通常不用于临床实践,因为它需要数据分析和解释方面的专业知识。将人工智能集成到IGA中可以改善脑卒中后临床步态评估,但以往的步态评估系统的临床实用性相对较低。本研究旨在开发一种基于知识图谱(KG)的面向临床的脑卒中后步态自动评估系统,以更好地支持临床医生。首先在步态分析领域建立了一个域KG。该系统可以处理IGA数据,基于运动学分析和KG识别步态异常及其潜在原因。对20名中风后患者和4名领域专家的初步评估测试了该系统在临床环境中的表现,显示平均召回率、准确率和f分数分别为1.78、0.89。4名临床专业人员表现出在临床环境中使用该系统的高行为意愿(基于技术接受模型的5点李克特量表为4.33±0.41)。结果表明,该系统有可能应用于临床环境,为临床医生提供有用的补充见解,这可能会促进对IGA的解释和临床应用。这种KG的模式可以推广或扩展到与其他疾病相关的步态分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A knowledge graph-based post-stroke gait assessment system: A pilot study
Instrumented gait analysis (IGA) has been widely used in research, but not typically in clinical practice, as it requires expertise in data analysis and interpretation. Post-stroke clinical gait assessment could be improved by integrating artificial intelligence into IGA, but previous gait assessment systems have relatively low clinical utility. This study aims to develop a clinically oriented automatic post-stroke gait assessment system based on knowledge graph (KG) to better support clinicians. A domain KG is first constructed in the field of gait analysis. This system can process IGA data to identify gait abnormalities and their potential causes based on kinematic analysis and KG. A preliminary evaluation with twenty post-stroke patients and four domain experts tested the system's performance in clinical settings, showing an average recall, precision, and F-score of 1, 0.78, and 0.89. Four clinical professionals showed high behavioural intention to use the system in clinical settings (4.33 ± 0.41 on a 5-point Likert scale based on the Technology Acceptance Model). The results depicted that this system has potential to be applied in clinical settings to provide useful supplementary insights for clinicians, which may promote the interpretation and clinical utility of IGA. The schema of this KG could be generalised or extended to gait analysis related to other diseases.
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来源期刊
Medical Engineering & Physics
Medical Engineering & Physics 工程技术-工程:生物医学
CiteScore
4.30
自引率
4.50%
发文量
172
审稿时长
3.0 months
期刊介绍: Medical Engineering & Physics provides a forum for the publication of the latest developments in biomedical engineering, and reflects the essential multidisciplinary nature of the subject. The journal publishes in-depth critical reviews, scientific papers and technical notes. Our focus encompasses the application of the basic principles of physics and engineering to the development of medical devices and technology, with the ultimate aim of producing improvements in the quality of health care.Topics covered include biomechanics, biomaterials, mechanobiology, rehabilitation engineering, biomedical signal processing and medical device development. Medical Engineering & Physics aims to keep both engineers and clinicians abreast of the latest applications of technology to health care.
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