Hevelius Report: Visualizing Web-Based Mobility Test Data For Clinical Decision and Learning Support
, 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...
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| Vydáno v: | ASSETS. Annual ACM Conference on Assistive Technologies Ročník 2024 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
01.10.2024
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| Témata: | |
| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Shrnutí: | , 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. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| DOI: | 10.1145/3663548.3688490 |