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赫维留斯报告:可视化基于网络的移动性测试数据以支持临床决策和学习

Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support.

作者信息

Lin Hongjin, Han Tessa, Gajos Krzysztof Z, Gupta Anoopum S

机构信息

School of Engineering and Applied Sciences, Harvard University, Allston, Massachusetts, United States.

Bioinformatics and Integrative Genomics, Harvard University, Cambridge, Massachusetts, United States.

出版信息

ASSETS. 2024 Oct;2024. doi: 10.1145/3663548.3688490. Epub 2024 Oct 27.

DOI:10.1145/3663548.3688490
PMID:40635767
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12239997/
Abstract

, a web-based computer mouse test, measures arm movement and has been shown to accurately evaluate severity for patients with Parkinson's disease and ataxias. A session produces 32 numeric features, which may be hard to interpret, especially in time-constrained clinical settings. This work aims to support clinicians (and other stakeholders) in interpreting and connecting features to clinical concepts. Through an iterative design process, we developed a visualization tool () that (1) abstracts six clinically relevant concepts from 32 features, (2) visualizes patient test results, and compares them to results from healthy controls and other patients, and (3) is an interactive app to meet the specific needs in different usage scenarios. Then, we conducted a preliminary user study through an online interview with three clinicians who were involved in the project. They expressed interest in using , especially for identifying subtle changes in their patients' mobility that are hard to capture with existing clinical tests. Future work will integrate the visualization tool into the current clinical workflow of a neurology team and conduct systematic evaluations of the tool's usefulness, usability, and effectiveness. represents a promising solution for analyzing fine-motor test results and monitoring patients' conditions and progressions.

摘要

一种基于网络的电脑鼠标测试,可测量手臂运动,并且已被证明能准确评估帕金森病和共济失调患者的病情严重程度。一次测试会产生32个数值特征,这些特征可能难以解读,尤其是在时间紧迫的临床环境中。这项工作旨在支持临床医生(及其他利益相关者)解读这些特征并将其与临床概念联系起来。通过反复的设计过程,我们开发了一种可视化工具(),该工具(1)从32个特征中提炼出六个与临床相关的概念,(2)可视化患者的测试结果,并将其与健康对照者及其他患者的结果进行比较,(3)是一个交互式应用程序,以满足不同使用场景下的特定需求。然后,我们通过对参与该项目的三位临床医生进行在线访谈开展了一项初步用户研究。他们对使用该工具表示出兴趣,特别是用于识别患者运动中现有临床测试难以捕捉到的细微变化。未来的工作将把该可视化工具整合到神经科团队当前的临床工作流程中,并对该工具的有用性、可用性和有效性进行系统评估。该工具是分析精细运动测试结果以及监测患者病情和进展的一个很有前景的解决方案。

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本文引用的文献

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Real-life ankle submovements and computer mouse use reflect patient-reported function in adult ataxias.现实生活中的踝关节子运动和电脑鼠标使用情况反映了成人共济失调患者自我报告的功能。
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