Evidence map›Paper›PMID 40436887›Full record

ArticleScientific data2025

A PPG Signal Dataset Collected in Semi-Naturalistic Settings Using Galaxy Watch.

Sangjun Park, Dejiang Zheng, Uichin Lee

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sangjun ParkKorea Advanced Institute of Science and Technology, School of Computing, Daejeon, 34141, South Korea.
Dejiang ZhengKorea Advanced Institute of Science and Technology, School of Computing, Daejeon, 34141, South Korea.
Uichin LeeKorea Advanced Institute of Science and Technology, School of Computing, Daejeon, 34141, South Korea. uclee@kaist.edu.

Funding

National Research Foundation of Korea (NRF) 2022R1A2C2011536
6 · The paper itself

Abstract

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.

Indexed as

PhotoplethysmographyWearable Electronic DevicesElectrocardiographyHeart RateHumans

Identifiers

PMID40436887
PMCPMC12119839

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.