Blood pressure assessment through photoplethysmographic data
Creators: name: Preciado, Valeria
name: Gutiérrez Ríos, Tatiana
Publisher: name: figshare
Year: 2024
Subjects: classificationCode: 320101
subject: Cardiology (incl. cardiovascular diseases)

description: With the aim of promoting research in the area of non-invasive blood pressure measurement, we present this data set that includes 46 blood pressure time series collected from healthy subjects in their daily life.<br>DescriptionThe sample for this evaluation was made up of 46 individuals, of which 32 were women and 14 men. In each one, recordings of PPG signals were taken to later estimate their blood pressure. Data was also collected to diagnose if they had any cardiovascular risk and if they were undergoing any treatment.The additional data collected is shown in the excel file "DATOS SUJETOS_21_06_2024_Sterol.xlsx":<br>Registration: Identification by #.Gender: F or M.Age: Range between 32 - 80 years.Weight: Range between 50 - 103 Kg.Height: Range 1.47 - 1.80.Medicated: Yes or no.Cholesterol: 135 - 333.Background of cholesterol contractionCholesterolLipids are essential biomolecules formed mainly by the union of thioester or isoprene units. These compounds, such as triglycerides and cholesterol, are vital for the functioning of living organisms.<br>This lipid is classified into two types: Low-density Lipoprotein (or LDL cholesterol, “bad cholesterol”), and High-density Lipoprotein (or HDL cholesterol, “good cholesterol”)<br><b>Colesterol LDL</b>&lt;100 Optico100 - 129 Cerca de optico130 - 159 Limite alto160 - 189 Alto240 Muy alto<b>Colestero Total</b>&lt;200 Deseable200 - 239 Limite alto240 Alto<b>Colesterol HDL</b>&lt;40 Bajo60 Alto<br>Photoplethysmography (PPG)PPG is based on the interaction of light with blood. An LED emits light that passes through the skin and is partially absorbed by hemoglobin in the blood. A sensor detects changes in the intensity of the reflected light, allowing information about blood flow to be obtained.PPG signal acquisitionTo acquire the PPG signal, an optical sensor is needed that includes an infrared emitter and phototransistor.<br>Para su leer archivos en paython o Matlab se suguiere utilizar los siguientes códigos:<b>Python:</b> se pueden utilizar las siguientes líneas de código:<pre><pre>import json<br>with open(r"Folder_Name/PPG_subj_##.json", "r") as j:<br> mydata = json.load(j)</pre></pre><b>Matlab:</b> puedes utilizar las siguientes líneas de código teniendo en la misma carpeta local los archivos JSON:<br><pre>json_file = fileread('PPG_subj_##.json');<br>ppg = jsondecode(json_file);</pre><br>REFERENCESSanvsquezsz. (s. f.-b). <i>GitHub - sanvsquezsz/PPG-based-BP-assessment: This data set contains PPG recordings from 56 subjects who were not hospitalized during data collection. This dataset is intended to support the development of approaches for blood pressure estimation by analyzing PPG signals.</i> GitHub. https://github.com/sanvsquezsz/PPG-based-BP-assessmentArgüello-Prada, E. J., Ibarra, K. D. M., &amp; Jiménez, K. L. D. (2024). The use of successive systolic differences in photoplethysmographic (PPG) signals for respiratory rate estimation. Heliyon, e26036. https://doi.org/10.1016/j.heliyon.2024.e26036<br><br>