Preliminary Diagnosis for Flu using Facial Feature Recognition and Thermal Camera
COVID-19 signs are similar to flu and their symptoms can range from no signs and symptoms (asymptomatic) to severe signs and symptoms (symptomatic). Fever, cough, fatigue, runny or stuffy nose, body aches, conjunctivitis, and headache are some of the symptoms that COVID-19 and flu have in common. Cu...
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Published in | 2021 5th International Conference on Electrical, Telecommunication and Computer Engineering (ELTICOM) Vol. 5; pp. 128 - 133 |
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Main Authors | , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
15.09.2021
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Subjects | |
Online Access | Get full text |
DOI | 10.1109/ELTICOM53303.2021.9590165 |
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Abstract | COVID-19 signs are similar to flu and their symptoms can range from no signs and symptoms (asymptomatic) to severe signs and symptoms (symptomatic). Fever, cough, fatigue, runny or stuffy nose, body aches, conjunctivitis, and headache are some of the symptoms that COVID-19 and flu have in common. Current technologies only take advantage of thermal sensors to identify the individual with possible flu-like symptoms. Adding extra layer of security in preventing the spread of diseases for people with flu-like symptoms must be set up at key locations using a video camera. The study can detect facial features such as reddish eyes, runny nose, dark circles around eyes and measure temperature using a non-contact thermal camera. Gathered image datasets were used for model training. Initial testing with the system revealed that closer distance and better illumination yielded better results upon consultation with a doctor using the comparison of 100 LUX and 1000 LUX lighting conditions. Validations were done using live video feeds where PCA and SVM were used for feature extraction and classification respectively. Support Vector Machine was used to evaluate subject whether they exhibited flu-like symptoms or not and compare the system output with doctors diagnosis. Error rates of 26.67% and 50% were achieved for False Acceptance and False Rejection Rates respectively along with 0% error rates for the temperature detection system. |
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AbstractList | COVID-19 signs are similar to flu and their symptoms can range from no signs and symptoms (asymptomatic) to severe signs and symptoms (symptomatic). Fever, cough, fatigue, runny or stuffy nose, body aches, conjunctivitis, and headache are some of the symptoms that COVID-19 and flu have in common. Current technologies only take advantage of thermal sensors to identify the individual with possible flu-like symptoms. Adding extra layer of security in preventing the spread of diseases for people with flu-like symptoms must be set up at key locations using a video camera. The study can detect facial features such as reddish eyes, runny nose, dark circles around eyes and measure temperature using a non-contact thermal camera. Gathered image datasets were used for model training. Initial testing with the system revealed that closer distance and better illumination yielded better results upon consultation with a doctor using the comparison of 100 LUX and 1000 LUX lighting conditions. Validations were done using live video feeds where PCA and SVM were used for feature extraction and classification respectively. Support Vector Machine was used to evaluate subject whether they exhibited flu-like symptoms or not and compare the system output with doctors diagnosis. Error rates of 26.67% and 50% were achieved for False Acceptance and False Rejection Rates respectively along with 0% error rates for the temperature detection system. |
Author | Dela Cruz, Jennifer C. Quintos, Jerome M. Dimaunahan, Ericson D. Luberia, Michael Anthony Y. |
Author_xml | – sequence: 1 givenname: Michael Anthony Y. surname: Luberia fullname: Luberia, Michael Anthony Y. email: mayluberia@mymail.mapua.edu.ph organization: School of EECE, Mapúa University,Manila,Philippines – sequence: 2 givenname: Jerome M. surname: Quintos fullname: Quintos, Jerome M. email: jmquintos@mymail.mapua.edu.ph organization: School of EECE, Mapúa University,Manila,Philippines – sequence: 3 givenname: Jennifer C. surname: Dela Cruz fullname: Dela Cruz, Jennifer C. email: jcdelacruz@mapua.edu.ph organization: School of EECE, Mapúa University,Manila,Philippines – sequence: 4 givenname: Ericson D. surname: Dimaunahan fullname: Dimaunahan, Ericson D. email: eddimaunahan@mapua.edu.ph organization: School of EECE, Mapúa University,Manila,Philippines |
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Snippet | COVID-19 signs are similar to flu and their symptoms can range from no signs and symptoms (asymptomatic) to severe signs and symptoms (symptomatic). Fever,... |
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SubjectTerms | COVID-19 Error analysis flu Lighting Medical services Nose PCA Support vector machines SVM symptoms temperature Temperature measurement |
Title | Preliminary Diagnosis for Flu using Facial Feature Recognition and Thermal Camera |
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