The dataset comprises 657 PPG waveform segments collected from 219 subjects, primarily aimed at aiding the non-invasive detection of cardiovascular disease and includes a variety of related health conditions.
Observational (n=219)
No
219 adult subjects in China, aged 21-86 years (median 58), 48% male, including individuals with normotension, prehypertension, stage I/II hypertension, diabetes, cerebral infarction, and insufficient brain blood supply.
Provides a publicly available, high-quality PPG and blood pressure dataset to facilitate research in non-invasive cardiovascular disease screening and blood pressure estimation.
Abstract Open clinical trial data provide a valuable opportunity for researchers worldwide to assess new hypotheses, validate published results, and collaborate for scientific advances in medical research. Here, we present a health dataset for the non-invasive detection of cardiovascular disease (CVD), containing 657 data segments from 219 subjects. The dataset covers an age range of 20–89 years and records of diseases including hypertension and diabetes. Data acquisition was carried out under the control of standard experimental conditions and specifications. This dataset can be used to carry out the study of photoplethysmograph (PPG) signal quality evaluation and to explore the intrinsic relationship between the PPG waveform and cardiovascular disease to discover and evaluate latent characteristic information contained in PPG signals. These data can also be used to study early and noninvasive screening of common CVD such as hypertension and other related CVD diseases such as diabetes.
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Liang et al. (Tue,) conducted a observational in Cardiovascular disease (CVD) (n=219). Photoplethysmography (PPG) vs. Blood pressure measurement using the Omron HEM-7201 was evaluated on Photoplethysmogram signal quality evaluation for estimating blood pressure and detecting cardiovascular disease.. The dataset comprises 657 PPG waveform segments collected from 219 subjects, primarily aimed at aiding the non-invasive detection of cardiovascular disease and includes a variety of related health conditions.
synapsesocial.com/papers/6968311cd43c56c1e0049ec4 — DOI: https://doi.org/10.1038/sdata.2018.20
Yongbo Liang
Guilin Medical University
Zhencheng Chen
Guangxi University
Guiyong Liu
Central South University
Scientific Data
University of British Columbia
British Columbia Children's Hospital
Guilin University of Electronic Technology
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