Data · dataset · 2026
BEmotion: A Real-World Data Collection for Emotion Recognition Using Smartwatches and Lessons Learned
Listed in RADAR and RADAR4Memory — shown once because both records carry DOI 10.35097/9c5yvpn5yqycd23s
Emotion recognition is important across healthcare, education, and daily life, but real-world deployment remains challenging.
Description
Collecting reliable biosignal and self-report data in natural settings poses key methodological and design challenges. We introduce "BEmotion", a dataset that links optical and kinematic biosignals to self-reported valence, arousal, and context.
The dataset was collected using smartwatches at three job fairs, involving \num{44} participants. While real-world datasets are essential, improved methods for collecting and using them are needed. Thus, we also analyze the challenges of real-world data collection encountered in the study.
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From these insights, we derive recommendations as well as lessons learned, and future use cases. We contribute: (1) with an open dataset and (2) recommendations for future dataset collections in the field. Furthermore, identify a need for greater personalization in emotion recognition rather than a one-fits-all recognition.
Links
Where it is published
- DOI doi.org/10.35097/9c5yvpn5yqycd23s ↗
DOI / persistent id · from radar service eu de
Catalogue records · 1
- OAI-PMH record radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=oai_dc&identifier… ↗
metadata API · from radar service eu de
Topics
- From keywords
- Computer Science & AI · Computer Science & AI · Earth & Environmental Science · Earth & Environmental Science
- Inferred from text
- Human-centred computing 75%
Provenance · 2 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| RADAR | 10.35097/9c5yvpn5yqycd23s | 13 d ago | JSON v1 |
| RADAR4Memory | 10.35097/9c5yvpn5yqycd23s | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| concepts[field].anzsrc:group:4608 | enrichment · radar service eu de | taxonomy-embedding@1.1.0 | title+keywords+description (75%) |
| concepts[field].local:field:computer-science-ai | mapping · radar4memory radar service eu | connector:radar4memory_radar_service_eu@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · radar4memory radar service eu | connector:radar4memory_radar_service_eu@1.0.0 | |
| description | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | /metadata/dc/description |
| license_text | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| publication_date | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | |
| title | source · radar service eu de | connector:radar_service_eu_de@1.0.0 | /metadata/dc/title |