A PPG Signal Dataset Collected in Semi-Naturalistic Settings Using Galaxy Watch
Open accessAbstract
The widespread adoption of consumer-grade wearable devices, such as Galaxy Watch, has revolutionized personal health monitoring as they enable continuous and non-invasive measurement of key cardiovascular indicators through photoplethysmography (PPG) sensors. However, existing datasets primarily rely on research-grade devices, limiting the applicability of consumer-grade wearables in real-world conditions. To address this gap, this study presents GalaxyPPG, a dataset collected from 24 participants that includes wrist-worn PPG signals from a Galaxy Watch 5 and an Empatica E4, alongside chest-worn ECG data from a Polar H10. Data were captured during diverse activities in a semi-naturalistic setting, providing insights into the sensing performance of consumer-grade wearables under motion- or stress-inducing activities. This dataset is designed to advance applications of PPG signals, such as HR tracking with diverse physical activities and HRV monitoring for stress detection. Additionally, we offer an open-source toolkit for data collection and analysis using Samsung Galaxy Watch, fostering reproducibility and further research leveraging this toolkit.
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Wearables may skip readings entirely when quality drops below internal thresholds, effectively masking rather than mitigating error.
“In some cases, wearables may even skip readings entirely when quality drops below internal thresholds, effectively masking rather than mitigating error [32].”
From PPG-Based Heart Rate Accuracy in Hispanic Adults with Fitzpatrick III–V Skin Tones: An Evaluation of Body Composition and Skin-Tone Effects (2026) · cites this paper as [32]
The Technical Validation section (Dataset Completeness Analysis; page unavailable) reports missing Galaxy Watch heart-rate measurements and says its internal status codes identify periods when the device deemed heart-rate calculations unreliable. It does not establish that readings were skipped because signal quality fell below an internal threshold, or characterize the missing readings as masking rather than mitigating error. (LLM, conf=0.85)
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- Authors
- Park, S., Zheng, D., & Lee, U.
- Affiliations
- Korea Advanced Institute of Science and Technology (KR)
- Corresponding author
- Lee, Uichin
- Venue
- Scientific Data
- Published
- 2025-05-28
- Volume
- 12
- Issue
- 1
- Pages
- 892-892
- ISSN
- 2052-4463 (ISSN-L)
- PMC
- PMC12119839
- OpenAlex
- W4410822879
- Cited by
- 12
- References
- 40
- Citations by year
- 2026: 10 · 2025: 2
- Type
- data paper
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Data (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research Foundation of Korea (2022R1A2C2011536)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- photoplethysmography, consumer-grade wearable devices, heart rate monitoring, heart rate variability, stress detection, physical activity, motion artifacts
- MeSH terms
- Wearable Electronic Devices, Electrocardiography, Heart Rate, Humans, Photoplethysmography
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