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Persistent Identifier
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doi:10.25824/redu/JTC3VH |
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Publication Date
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2026-09-01 |
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Title
| Viva Bem Light-to-vigorous physical activities dataset |
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Author
| Lima, Caíque Santos (Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação) - ORCID: https://orcid.org/0000-0002-9587-1823
Von Zuben, Fernando José (Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação) - ORCID: https://orcid.org/0000-0002-4128-5415
Bertocco, Felipe Capiteli (Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação) - ORCID: https://orcid.org/0000-0003-3645-4840
Oliveira, José Igor Vasconcelos de (Universidade Estadual de Campinas (UNICAMP). Faculdade de Educação Física) - ORCID: https://orcid.org/0000-0002-0034-9638
Souza, Thiago Mattos Frota de (Universidade Estadual de Campinas (UNICAMP). Faculdade de Educação Física) - ORCID: https://orcid.org/0000-0003-1464-8628
Silva, Emely Pujólli da (Universidade Estadual de Campinas (UNICAMP). Instituto de Computação) - ORCID: https://orcid.org/0000-0001-7745-6151 |
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Point of Contact
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Use email button above to contact.
Von Zuben, Fernando José (Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação) |
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Description
| This dataset consists of synchronized, high-frequency heart rate (HR) time-series data designed to evaluate the accuracy and motion-noise resilience of the Samsung Galaxy Watch 4 (SGW4) smartwatch against the industry-standard Polar H10 ECG chest strap. Collected at a sampling rate of 1 Hz via the Viva Sensing application, the dataset captures broad heart rate dynamics across light, moderate, and vigorous intensities during supervised 10-minute sessions of stationary cycling and treadmill workouts. The target population comprises healthy adult volunteers recruited under approved human research ethics guidelines (CAAE: 55532622.0.0000.5404), ensuring a cohort free of cardiorespiratory conditions or physical limitations that could affect the protocol's execution.To facilitate advanced validation and algorithm benchmarking, the dataset features precise contextual annotations regarding exercise type, target intensity zones calculated using the standard formula, and specific physical constraints. A key characteristic of this database is the inclusion of two distinct experimental scenarios for each activity: one where subjects restricted their arm movements to minimize external noise, and another where they moved naturally. This deliberate variation in motion artifacts makes the "Viva bem database" a valuable asset for researchers in digital health, biomedical engineering, and wearable technology seeking to develop and test filtering algorithms or machine learning models for photoplethysmography (PPG) sensors. Due to privacy and ethical considerations, only a portion of the dataset may be publicly available. Researchers interested in accessing the complete dataset should contact the authors and submit a formal request, which will be verified on a case-by-case basis to ensure compliance with privacy and ethical standards. The PGD is made available here (2026-06-12) |
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Subject
| Computer and Information Science; Medicine, Health and Life Sciences |
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Keyword
| Wearable devices
Heart rate monitoring
Biomedical measurement
Time series analysis (DLC (LCSH))
Artifacts (Signal processing) |
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Related Publication
| Lima, C. S., Bertocco, F. C., de Oliveira, J. I. V., de Souza, T. M. F., da Silva, E. P., & Von Zuben, F. J. (2024). Assessment of Samsung Galaxy Watch4 PPG-based heart rate during light-to-vigorous physical activities. IEEE Sensors Letters, 8(7), 1-4. doi: 10.1109/LSENS.2024.3408089 https://ieeexplore.ieee.org/document/10543174 |
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Contributor
| Convênio Samsung/Unicamp: 23/2021 |
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Funding Information
| No Funder: 0000 |
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Depositor
| Pujolli da Silva, Emely |
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Deposit Date
| 2026-06-12 |
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Declarações obrigatórias sobre ética e privacidade
| o projeto que gerou os dados foi aprovado pelo Comite de Ética em Pesquisa da Unicamp ou não envolve questões que requeiram tal aprovação; os dados que serão depositados estão de acordo com a LGPD (Lei Geral de Proteção de Dados) |