Related Experiment Video
Updated: May 31, 2026

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
Published on: February 3, 2022
Human experience in regulated offices (HERO) dataset: Synchronized multimodal physiological, environmental,
Puneet Tomar1, Dianel Ago2, Ilaria Pigliautile1
1EAPlab at CIRIAF Interuniversity Research Centre of Pollution and Environment Mauro Felli, University of Perugia, Italy.
Abstract:
The Human Experience in Regulated Offices (HERO) dataset is a synchronized, multimodal resource dataset designed to characterize human physiological and perceptual dynamics during realistic office activities in a controlled indoor setting. The dataset comprises data gathered on 24 voluntary healthy adults, each completing two laboratory sessions under distinct thermal regimens: Lower Temperature (LT; 22-24 °C) and Higher Temperature (HT; 30-32 °C), regulated within ±0.5 °C, conducted during the summer season in Köppen-Geiger Csa climate classification (temperate with dry and hot summer). In each session, participants followed a standardized nine-phase office-work protocol comprising an acclimation baseline, activity blocks, and interleaved washout periods, enabling analyses that explicitly account for activity type, sequencing, and recovery. The release integrates four-channel electroencephalography (EEG) acquired with a Muse-2 headband, electrodermal activity (EDA), and peripheral skin temperature (ST) recorded using an EmotiBit wrist-worn wearable sensor, indoor multi-domain environmental measurements acquired via the NEXT.ROOM facility, and phase-aligned surveys capturing multi-domain perceptions of the indoor environment and task experience. Visual context, such as, derived video quality check (QC)/coverage features, was recorded using laptop webcams. All data are distributed as level-0 device exports, restricted to the experimental window and enriched with consistent session identifiers and phase labels, while intentionally avoiding downstream preprocessing choices. The dataset is archived on Zenodo (DOI: 10.5281/zenodo.17957768) with documentation and code in the associated project's GitHub repository.
