TY - JOUR
T1 - Upper body thermal images and associated clinical data from a pilot cohort study of COVID-19
AU - Rojas-Zumbado, Sofia
AU - Tamez-Peña, Jose Gerardo
AU - Trevino-Ferrer, Andrea Alejandra
AU - Diaz-Garza, Carlos Andres
AU - Ledesma-Hernández, Meritxell
AU - Esparza-Sandoval, Alejandra Celina
AU - Ortiz-Lopez, Rocio
AU - Torre-Amione, Guillermo
AU - Cardona-Huerta, Servando
AU - Trevino, Victor
N1 - Funding Information:
We thank the staff from Hospital Zambrano-Hellion, especially Ricardo Marroquin, Adrian Flores, Myriam Madelon Marcos, and Laura Garcia, for providing kind assistance during the project development. We thank Carolina Tamez-Gonzalez and Patricia Gonzalez-Cerna for transcribing and correcting clinical databases. We thank Ignacio Fuentes for organizing the transport of cameras. We thank Andrea Celis-Terán for the artistic 3D scene representation of the body and video acquisition. We thank Adam Yala for his assistance in deciding on the thermal imaging equipment and Regina Barzilay for her help as part of the conceptualization team.
Publisher Copyright:
© 2024, The Author(s).
PY - 2024/1
Y1 - 2024/1
N2 - 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.
AB - 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.
KW - Covid-19
KW - Demographic data
KW - Respiratory disease
KW - Thermal imaging
KW - Thermal videos
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U2 - 10.1186/s13104-024-06688-w
DO - 10.1186/s13104-024-06688-w
M3 - Article
C2 - 38243331
AN - SCOPUS:85182642979
SN - 1756-0500
VL - 17
JO - BMC Research Notes
JF - BMC Research Notes
IS - 1
M1 - 30
ER -