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Data in brief · 2026

Human experience in regulated offices (HERO) dataset: Synchronized multimodal physiological, environmental, perceptual, and video-derived measurements across structured office activities in a controlled indoor setting.

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Tomar Puneet, Ago Dianel, Pigliautile Ilaria, Cosoli Gloria, Gnecco Veronica Martins, Casaccia Sara, Sartini Gianluca, Mansi Silvia Angela, Pisello Anna Laura, Arnesano Marco

Аннотация

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.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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