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CLBP-400: A Real-World Video Dataset for Cuff-Less Blood Pressure Estimation via rPPG

The development of remote blood pressure (BP) measurement algorithms using remote photoplethysmography (rPPG) has significant limitations, including the small size of publicly available datasets, privacy concerns regarding facial videos, and a lack of diverse, realistic datasets associated with a

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CreatorAl-Naji, Ali Abdulelah
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Published2026-04-15
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DOI10.20944/preprints202604.1079.v1
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Downloads119
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Licensecc-by-4.0
File Size777.5 MB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views215
Total Downloads119

The development of remote blood pressure (BP) measurement algorithms using remote photoplethysmography (rPPG) has significant limitations, including the small size of publicly available datasets, privacy concerns regarding facial videos, and a lack of diverse, realistic datasets associated with actual BP measurements. To address these challenges, this study aimed to provide comprehensive, simultaneous recordings of participants’ faces, along with reference physiological measurements, for 400 adult participants aged 18–79 years. For each imaging session, systolic and diastolic blood pressure and reference heart rate (HR) were recorded using clinical electronic BP monitors in addition to recording illuminance (lux) values for indoor and outdoor environments. The collected data, called CLBP-400, is a crucial resource for developing and evaluating remote vital signs from facial rPPG signals. A sample of videos is publicly available to demonstrate data quality, while academic researchers can access the complete dataset under a strict data use agreement.

Access to Full Dataset: The full CLBP-400 dataset (400 high-quality videos and physiological metadata) is not hosted directly on Zenodo to ensure participant privacy and data integrity.

To request access to the complete dataset, please visit our official project website:

CLBP-300

 

Table 1. Specification Table.

Task

Description

Acronym

CLBP-400.

Beneficiaries

Digital Health Researchers, AI & Computer Vision Developers and Computer Science Researchers.

Specific subject area

Digital Health / Health Informatics and AI in Medicine.

Total participants

400 (289 Males, 111 Females)

Duration

30-60 seconds per video.

Type of data

Videos and excel sheet providing ground-truth measurements for SYSBP, DIABP, and HR for each recorded video with ambient light intensity recorded in Lux and demographic attributes for each participant (i.e. age and gender).

How data were acquired

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Files are hosted on the source repository. Click download to access the full dataset.

Al-Naji, Ali Abdulelah (2026). CLBP-400: A Real-World Video Dataset for Cuff-Less Blood Pressure Estimation via rPPG. https://doi.org/10.20944/preprints202604.1079.v1