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Guanghao Sun, Yu Yao, Ritsu Yoshinaka, Mayumi Ikegami, Seokjin Kim, Michael Schiek and Takemi Matsui
Background: Seasonal influenza virus outbreaks cause annual epidemics, mostly during winter in temperate zone countries, especially resulting in increased morbidity and higher mortality in children. In order to conduct rapid screening for influenza in pediatric outpatient units, we developed a pediatric infection screening system with a radar respiration monitor.
Methods: The system conducts influenza screening within 10 seconds based on vital signs (i.e., respiration rate monitored using a 24 GHz microwave radar; facial temperature, using a thermopile array; and heart rate, using a pulse photosensor). A support vector machine (SVM) classification method was used to discriminate influenza children from healthy children based on vital signs. To assess the classification performance of the screening system that uses the SVM, we conducted influenza screening for 70 children (i.e., 27 seasonal influenza patients (11 ± 2 years) at a pediatric clinic and 43 healthy control subjects (9 ± 4 years) at a pediatric dental clinic) in the winter of 2013-2014.
Results: The screening system using the SVM identified 26 subjects with influenza (22 of the 27 influenza patients and 4 of the 43 healthy subjects). The system discriminated 44 subjects as healthy (5 of the 27 influenza patients and 39 of the 43 healthy subjects), with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 81.5%, 90.7%, 84.6%, and 88.6%, respectively.
Conclusion: The SVM-based screening system achieved classification results for the outpatient children based on vital signs with comparatively high NPV within 10 seconds. At pediatric clinics and hospitals, our system seems potentially useful in the first screening step for infections in the future.