Upper body thermal images and associated clinical data from a pilot cohort study of COVID-19 - Rojas-Zumbado, Sofia; Tamez-Peña, Jose-Gerardo; Trevino-Ferrer, Andrea-Alejandra; Diaz-Garza, Carlos-Andres; Ledesma-Hernández, Meritxell; Esparza-Sandoval, Alejandra-Celina; Ortiz-Lopez, Rocio; Torre-Amione, Guillermo; Cardona-Huerta, Servando; Trevino, Victor (BMC research notes, 2024)
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.