PD-Insighter: A Visual Analytics System to Monitor Daily Actions for Parkinson's Disease Treatment
Proceedings of the CHI Conference on Human Factors in Computing Systems(2024)
摘要
People with Parkinson's Disease (PD) can slow the progression of their
symptoms with physical therapy. However, clinicians lack insight into patients'
motor function during daily life, preventing them from tailoring treatment
protocols to patient needs. This paper introduces PD-Insighter, a system for
comprehensive analysis of a person's daily movements for clinical review and
decision-making. PD-Insighter provides an overview dashboard for discovering
motor patterns and identifying critical deficits during activities of daily
living and an immersive replay for closely studying the patient's body
movements with environmental context. Developed using an iterative design study
methodology in consultation with clinicians, we found that PD-Insighter's
ability to aggregate and display data with respect to time, actions, and local
environment enabled clinicians to assess a person's overall functioning during
daily life outside the clinic. PD-Insighter's design offers future guidance for
generalized multiperspective body motion analytics, which may significantly
improve clinical decision-making and slow the functional decline of PD and
other medical conditions.
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