Demo Data from SIGIR 2026 / reviewers in the wild / expert
Luca Cornia
dblp:371/1476
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0009-4999-1726ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-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 |
Wearable and physiological sensing · 87% Health and well-being technologies · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wearable and physiological sensing › cognitive state monitoring
fatigue detection |
0.8 | 1 | 2024 | Understanding Fatigue Through Biosignals: A Comprehensive Dataset · HRI 2024 |
Health and well-being technologies › health monitoring
fatigue monitoring |
0.2 | 1 | 2024 | Understanding Fatigue Through Biosignals: A Comprehensive Dataset · HRI 2024 |
Methods — techniques the papers use, named apart from their topics
eye tracking · 0.8electromyography · 0.8electrodermal activity · 0.8electrocardiography · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Understanding Fatigue Through Biosignals: A Comprehensive DatasetabstractFatigue is a multifaceted construct, that represents an important part of human experience. The two main aspects of fatigue are the mental one and the physical one, that often intertwine, intensifying their collective impact on daily life and overall well-being. To soften this impact, understanding and quantifying fatigue is crucial. Physiological data play a pivotal role in the comprehension of fatigue, allowing a precious insight into the level and type of fatigue experienced. Though the analysis of these biosignals, researchers can determine whether the person is feeling mental fatigue, physical fatigue or a combination of both. This paper introduces MePhy, a comprehensive dataset containing various biosignals, gathered while inducing different fatigue conditions, in particular mental and physical fatigue. Among the biosignals closely associated with stress situations, we chose: eye activity, cardiac activity, electrodermal activity (EDA) and electromyography (EMG). Data were collected using different devices, including a camera, a chest strap and different sensors from the BITalino kit. Marta Gabbi, Luca Cornia, Valeria Villani, Lorenzo Sabattini |
HRI | 2 |