Upper body thermal images and associated clinical data from a pilot cohort study of COVID-19

Autor: Sofia Rojas-Zumbado, Jose-Gerardo Tamez-Peña, Andrea-Alejandra Trevino-Ferrer, Carlos-Andres Diaz-Garza, Meritxell Ledesma-Hernández, Alejandra-Celina Esparza-Sandoval, Rocio Ortiz-Lopez, Guillermo Torre-Amione, Servando Cardona-Huerta, Victor Trevino
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: BMC Research Notes, Vol 17, Iss 1, Pp 1-4 (2024)
Druh dokumentu: article
ISSN: 1756-0500
DOI: 10.1186/s13104-024-06688-w
Popis: Abstract Objectives The data was collected for a cohort study to assess the capability of thermal videos in the detection of SARS-CoV-2. Using this data, a published study applied machine learning to analyze thermal image features for Covid-19 detection. Data description The study recorded a set of measurements from 252 participants over 18 years of age requesting a SARS-CoV-2 PCR (polymerase chain reaction) test at the Hospital Zambrano-Hellion in Nuevo León, México. Data for PCR results, demographics, vital signs, food intake, activities and lifestyle factors, recently taken medications, respiratory and general symptoms, and a thermal video session where the volunteers performed a simple breath-hold in four different positions were collected. Vital signs recorded include axillary temperature, blood pressure, heart rate, and oxygen saturation. Each thermal video is split into 4 scenes, corresponding to front, back, left and right sides, and is available in MPEG-4 format to facilitate inclusion into pipelines for image processing. Raw JPEG images of the background between subjects are included to register variations in room temperatures.
Databáze: Directory of Open Access Journals
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