Author: Yang, Xiaofeng; Ishibashi, Koichiro; Hoi, Le; Vu, Trung Nguyen; Nguyen Van, Kinh; Sun, Guanghao
Title: Dengue Fever Detecting System Using Peak-detection of Data from Contactless Doppler Radar. Cord-id: 3ncyfw35 Document date: 2018_1_1
ID: 3ncyfw35
Snippet: Infectious diseases, such as dengue fever and Middle East respiratory syndrome, have become prevalent worldwide in recent times. To conduct highly accurate and effective infection screening, we are working on the development of a contactless infection screening system using Doppler radar and thermography. In our previous work, three parameters (face temperature, heartbeat rate, and respiration rate) were used to judge whether a subject was infected. However, facial temperature measurements may b
Document: Infectious diseases, such as dengue fever and Middle East respiratory syndrome, have become prevalent worldwide in recent times. To conduct highly accurate and effective infection screening, we are working on the development of a contactless infection screening system using Doppler radar and thermography. In our previous work, three parameters (face temperature, heartbeat rate, and respiration rate) were used to judge whether a subject was infected. However, facial temperature measurements may be vastly different from temperatures measured at the axilla owing to influence from the immediate environment. In this study, heartbeat rate (HR), respiration rate (RR), and standard deviation of heartbeat interval (SDHI) were used to quantify the infection screening system without using facial temperature as a parameter. We found that respiratory sinus arrhythmia (RSA) diminished in patients who had dengue fever. We gathered data from 47 patients with dengue fever using a 10-GHz Doppler radar system at the National Hospital of Tropical Diseases (NHTD) in Hanoi, Vietnam. To evaluate the accuracy, the data of these patients were compared to that of 23 unaffected subjects. We observed that a linear discriminant analysis (LDA) was effective at detecting the dengue fever conditions, and the detection accuracy was approximately 97.6%.
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