Demo Data from EDBT 2026 / reviewers in the wild / expert
Howard Jiang
dblp:347/2928
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Health and well-being technologies · 77% Wearable and physiological sensing · 23% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Health and well-being technologies › health monitoring
parkinson's disease monitoring |
0.8 | 1 | 2024 | PD-Insighter: A Visual Analytics System to Monitor Daily Actions for Parkinson's Disease Treatment · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
iterative design study · 1.5immersive replay · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | PD-Insighter: A Visual Analytics System to Monitor Daily Actions for Parkinson's Disease TreatmentabstractPeople 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. Jade Kandel, Chelsea Duppen, Qian Zhang 0066, Howard Jiang, Angelos Angelopoulos, Ashley Paula-Ann Neall, Pranav Wagh, Daniel Szafir, Henry Fuchs, Michael Lewek, Danielle Albers Szafir |
CHI | 4 |