Jessica R. Blumberg

dblp:402/8876 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0003-6977-0855ORCID · reported

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% Human-AI interaction · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies
chronic illness management
0.912025
The Voice of Endo: Leveraging Speech for an Intelligent System That Can Forecast Illness Flare-ups · CHI 2025
Human-AI interaction
human-centered AI
0.312025
The Voice of Endo: Leveraging Speech for an Intelligent System That Can Forecast Illness Flare-ups · CHI 2025

Methods — techniques the papers use, named apart from their topics

speech analysis · 0.9speculative design · 0.9
YearPublicationVenuePosition
2025 The Voice of Endo: Leveraging Speech for an Intelligent System That Can Forecast Illness Flare-ups
abstract
Managing complex chronic illness is challenging due to its unpredictability. This paper explores the potential of voice for automated flare-up forecasts. We conducted a six-week speculative design study with individuals with endometriosis, tasking participants to submit daily voice recordings and symptom logs. Through focus groups, we elicited their experiences with voice capture and perceptions of its usefulness in forecasting flare-ups. Participants were enthusiastic and intrigued at the potential of flare-up forecasts through the analysis of their voice. They highlighted imagined benefits from the experience of recording in supporting emotional aspects of illness and validating both day-to-day and overall illness experiences. Participants reported that their recordings revolved around their endometriosis, suggesting that the recordings' content could further inform forecasting. We discuss potential opportunities and challenges in leveraging the voice as a data modality in human-centered AI tools that support individuals with complex chronic conditions.
Adrienne Pichon, Jessica R. Blumberg, Lena Mamykina, Noémie Elhadad
CHI2