{"title":"使用Galaxy Watch在半自然环境下收集的PPG信号数据集。","authors":"Sangjun Park, Dejiang Zheng, Uichin Lee","doi":"10.1038/s41597-025-05152-z","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"892"},"PeriodicalIF":5.8000,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12119839/pdf/","citationCount":"0","resultStr":"{\"title\":\"A PPG Signal Dataset Collected in Semi-Naturalistic Settings Using Galaxy Watch.\",\"authors\":\"Sangjun Park, Dejiang Zheng, Uichin Lee\",\"doi\":\"10.1038/s41597-025-05152-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":21597,\"journal\":{\"name\":\"Scientific Data\",\"volume\":\"12 1\",\"pages\":\"892\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12119839/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Data\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41597-025-05152-z\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-05152-z","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
A PPG Signal Dataset Collected in Semi-Naturalistic Settings Using Galaxy Watch.
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.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.