ConGaIT: A Clinician-Centered Dashboard for Contestable AI in Parkinson's Disease Care

AI-assisted gait analysis holds promise for improving Parkinson's Disease (PD) care, but current clinical dashboards lack transparency and offer no meaningful way for clinicians to interrogate or contest AI decisions. We present Con-GaIT (Contestable Gait Interpretation & Tracking), a clinician-centered system that advances Contestable AI through a tightly integrated interface designed for interpretability, oversight, and procedural recourse. Grounded in HCI principles, ConGaIT enables structured disagreement via a novel Contest & Justify interaction pattern, supported by visual explanations, role-based feedback, and traceable justification logs. Evaluated using the Contestability Assessment Score (CAS), the framework achieves a score of 0.970, demonstrating that contestability can be operationalized through human-centered design in compliance with emerging regulatory standards. A demonstration of the framework is available at https://github.com/hungdothanh/Con-GaIT.

Publication Details

Journal
ArXiv.org
Published
2025-07-30
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
Field-Weighted Citation Impact
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article

ConGaIT: A Clinician-Centered Dashboard for Contestable AI in Parkinson's Disease Care

ArXiv.org
Balance, Gait, and Falls Prevention
article

ConGaIT: A Clinician-Centered Dashboard for Contestable AI in Parkinson's Disease Care

article en

Abstract

AI-assisted gait analysis holds promise for improving Parkinson's Disease (PD) care, but current clinical dashboards lack transparency and offer no meaningful way for clinicians to interrogate or contest AI decisions. We present Con-GaIT (Contestable Gait Interpretation & Tracking), a clinician-centered system that advances Contestable AI through a tightly integrated interface designed for interpretability, oversight, and procedural recourse. Grounded in HCI principles, ConGaIT enables structured disagreement via a novel Contest & Justify interaction pattern, supported by visual explanations, role-based feedback, and traceable justification logs. Evaluated using the Contestability Assessment Score (CAS), the framework achieves a score of 0.970, demonstrating that contestability can be operationalized through human-centered design in compliance with emerging regulatory standards. A demonstration of the framework is available at https://github.com/hungdothanh/Con-GaIT.

ArXiv.org
Openalex Percentile: Top 35%
Balance, Gait, and Falls Prevention
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ConGaIT: A Clinician-Centered Dashboard for Contestable AI in Parkinson's Disease Care · ArXiv.org (2025) | TGRS Research Map | TGRS