Data · dataset · 2025
CATSA: A Wrist Worn Wearable Dataset for Stress Analysis
Listed in Teesside University Research Data Repository
The CATSA dataset is a publicly accessible multimodal dataset comprising wearable signals designed for stress and cognitive task analysis.
Description
It primarily captures physiological responses under baseline conditions and during induced cognitive tasks from a wearable device. The dataset is organized within a root folder named CATSA, which contains 50 subfolders, each corresponding to an individual participant and labeled as subXY, where XY represents an incrementing numerical identifier.
Within each participant’s folder, there are four subdirectories named Baseline, Stroop, Logic, and Sudoku, corresponding to different experimental conditions. Each of these subdirectories contains five CSV files that store data recorded by the wrist-worn Empatica E4 device, including Blood Volume Pulse (BVP), Electrodermal Activity (EDA), Accelerometer data (ACC), Body Temperature (TEMP), and Heart Rate (HR).
Links
Where it is published
- DOI doi.org/10.17632/g7vbwsxzcy.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Affective computing · Biomedical engineering · Computer Science & AI · Earth & Environmental Science · Electrical engineering · Engineering · Machine learning · Signal processing
- Inferred from text
- Heart 75%
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/g7vbwsxzcy.1 | 16 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[anatomy].local:anatomy:heart | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:field:400607 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Signal Processing'] |
| concepts[field].anzsrc:field:460802 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Affective Computing'] |
| concepts[field].anzsrc:group:4003 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Biomedical Engineering'] |
| concepts[field].anzsrc:group:4008 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Electrical Engineering'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |