Demo Data from SIGIR 2026 / reviewers in the wild / expert
Nelson Hidalgo
dblp:318/7975
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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 · 44% Immersive interaction · 44% Health and well-being technologies · 13% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wearable and physiological sensing
physiological computing |
0.6 | 1 | 2022 | Galea: A physiological sensing system for behavioral research in Virtual Environments · VR 2022 |
Methods — techniques the papers use, named apart from their topics
multimodal signal acquisition · 0.6biosensors · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Galea: A physiological sensing system for behavioral research in Virtual EnvironmentsabstractThe pairing of Virtual Reality technology with Physiological Sensing has gained much interest in clinical settings and beyond: from developing novel methods for diagnosis of perception and cognition impairments, biofeedback for anxiety treatment, to enhancing everyday practices such as self-guided meditation. However, conducting this type of research does not come without challenges. For example, accessing the equipment for recording data from the user and synchronizing physiological response data with the stimuli or interactive environment are not trivial tasks, and generating virtual content in response to the user’s real-time data is costly and complex. This paper presents Galea, a device for multi-modal signal acquisition able to measure the physiological response of a user when experiencing virtual content, enabling behavioral, affective computing , and human-computer interaction research and applications to access data from the Parasympathetic nervous system and Sympathetic nervous system simultaneously. We present a primer on detectable human physiology as an input source for Physiological Computing from the perspective of the signals available through our device. We describe the primary design considerations and circuit characterization results of in-vivo recordings from the wearer’s brain, eyes, heart, skin, and muscles. We also present an example to help contextualize how these signals can be used in a virtual reality setting. Galea makes working with physiological sensors in virtual reality more accessible and can offer a standard for inter and intra experiment data comparisons. Lastly, we discuss the importance and contributions of this work as well as future challenges that need to be considered. Guillermo Bernal, Nelson Hidalgo, Conor Russomanno, Pattie Maes |
VR | 2 |